Best AI Staffing Agencies in 2026
Independent reviews of 33 agencies that place ML, LLM, MLOps and data engineers inside your team, judged on how fast they fill a seat, who does the technical screening, and what happens when a hire doesn't work out.
Which AI staffing agency is best?
Short answer: Tensorway is the best fit for most product teams adding AI engineers. Beyond that, the right pick depends on how many seats you need, how fast, and whether you want employees or freelancers.
- Best overall: Tensorway – Engineer-led screening with a free replacement if a hire doesn't fit
- Best for filling several seats on U.S. hours: BairesDev – Largest employed LatAm engineering bench on this list
- Best for a hard modeling problem: deepsense.ai – Research-grade data scientists available as embedded team members
- Best for transparent nearshore pricing: Howdy.com – Published 15% fee on top of the engineer's pay
- Best for a short freelance engagement: Toptal – Fast access to screened freelancers with a no-risk trial
- Best for hiring onto your own payroll: KORE1 – Direct-hire and contract-to-hire paths for AI roles
How do the top AI staffing agencies compare?
All 33 agencies, in rank order. Most quote rates only after a discovery call, so the pricing column shows how each one bills.
| Company | Best for | Pricing model | Min. engagement | Rating |
|---|---|---|---|---|
| Tensorway Editor's pick | Product teams adding AI engineers fast, two-week trial | Monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request | Not disclosed | |
| deepsense.ai Editor's pick | Research-heavy ML problems, senior data scientists | Time and materials; dedicated team; rates on request | Not disclosed | |
| BairesDev Editor's pick | U.S. companies needing several engineers in American time zones | Monthly per engineer; dedicated teams; rates on request | Not disclosed | |
| Startups adding GenAI engineers on U.S. hours | Monthly per engineer; dedicated team; project-based; rates on request | Not disclosed | | |
| Data-science-heavy teams, AWS-based ML work | Dedicated team; time and materials; project budgets from under $50K per Clutch | Not disclosed | | |
| Retail and fitness products, one AI engineer to start | Monthly per engineer; dedicated team; rates on request | 1 full-time engineer | | |
| Python-heavy AI products, quick shortlist | Monthly per engineer; squads of 3–8; from about $50–$99/hr per company pricing page | 1 engineer | | |
| Enterprises scaling data and ML teams in Europe | Time and materials; dedicated team; rates on request | Not disclosed | | |
| U.S. scale-ups hiring long-term LatAm AI engineers | Monthly per engineer; rates on request after a discovery call | Not disclosed | | |
| Ad-tech and high-volume data teams | Time and materials; staff augmentation; rates on request | Not disclosed | | |
| Companies wanting both Mexican and Polish delivery options | Time and materials; dedicated team; rates on request | Not disclosed | | |
| Budget-conscious teams hiring a dedicated AI developer | Monthly per dedicated developer; part-time consultants; $25–$49/hr (third-party directory band) | 1 dedicated developer | | |
| Startups and scale-ups wanting CVs within two days | Monthly per engineer; dedicated team; rates on request | 1 developer | | |
| Product teams adding GenAI to an existing app | Time and materials; team extension; $50–$99/hr (Clutch band) | $10K | | |
| Python product teams adding ML capacity | Time and materials; team extension; rates on request | Not disclosed | | |
| Banks, insurers and fintechs building AI features | Time and materials; fixed-term staff augmentation; rates on request | Not disclosed | | |
| Teams that want transparent nearshore pricing | Engineer salary plus a flat 15% service fee (published) | 1 engineer | | |
| Short engagements with a senior freelance specialist | Hourly, part-time or full-time contracts; deposit required; rates not published | Not disclosed | | |
| Companies wanting LLM-savvy contractors from a large pool | Hourly or monthly contracts; rates on request | Not disclosed | | |
| Azure-based companies wanting a lower-cost dedicated AI team | Dedicated team; time and materials; rates on request | Not disclosed | | |
| Enterprises needing many seats filled within days | Time and materials; dedicated team; rates on request | Not disclosed | | |
| Media and gaming teams adding long-term remote developers | Monthly per developer; squads; rates on request | Not disclosed | | |
| Consumer brands adding AI to digital products | Time and materials; team augmentation; rates on request | Not disclosed | | |
| Automotive and mobility companies, embedded AI | Dedicated team; AI pods; rates on request | Not disclosed | | |
| Regulated industries hiring experienced data scientists | Time and materials; rates sent with CVs | Not disclosed | | |
| Distributed teams hiring vetted contractors worldwide | Monthly or hourly contracts; rates on request | Not disclosed | | |
| Financial and travel firms needing long-lived dedicated teams | Dedicated development center; time and materials; rates on request | Not disclosed | | |
| U.S. companies that want to hire AI engineers onto payroll | Contract bill rate or direct-hire placement fee; rates on request | Not disclosed | | |
| Companies hiring LatAm developers without a local entity | Monthly per developer including payroll and compliance; rates on request | Not disclosed | | |
| Global enterprises with large, compliance-heavy AI programs | Enterprise time and materials; dedicated teams; rates on request | Not disclosed | | |
| Enterprises open to outcome-priced AI delivery | AI Pods subscription based on token consumption; traditional dedicated teams | Not disclosed | | |
| Microsoft-stack enterprises adding AI to Dynamics or Power Platform | Time and materials; dedicated team; rates on request | Not disclosed | | |
| Companies already using The Hackett Group or ZBrain | Dedicated developers; fixed project; rates on request | Not disclosed | |
What separates a good AI staffing agency from a CV broker?
Start with who runs the technical screen. At some agencies a recruiter scans a CV for keywords and forwards anything that mentions PyTorch. At others a working ML engineer reviews the candidate's code and sets a practical task before a profile ever reaches you. Sales decks make the two sound identical, so ask for the actual screening steps and the job title of the person who runs each one. If the answer is a recruiter plus an online quiz, plan on doing the hard technical interview yourself.
Employment model comes next. BairesDev, Innowise and Howdy.com employ their engineers, so payroll, local contracts and benefits are their problem, and so is turnover. Toptal, Turing and Andela work differently: they connect you with independent contractors. That route is quicker for a single specialist. It is much weaker on continuity, because when a freelancer moves on, whatever they knew about your system leaves with them unless someone wrote it down.
Then read the replacement terms. Even careful agencies make bad matches. A good one will put in writing what happens when a hire doesn't work out in the first weeks: who pays for the overlap, how quickly a replacement arrives, and whether you can scale down between sprints. Vague answers usually mean the risk sits with you.
Which frameworks and platforms do each agency's engineers use?
Short answer: nearly everyone here works in Python with PyTorch or TensorFlow. The useful differences are in cloud platform (AWS, Azure or Google Cloud) and LLM tooling, so match those to your own stack.
| Company | Primary tech stack |
|---|---|
| Tensorway | PyTorch, TensorFlow, LangChain, Hugging Face, OpenAI |
| deepsense.ai | PyTorch, TensorFlow, Hugging Face, LangChain, AWS SageMaker |
| BairesDev | Python, TensorFlow, PyTorch, AWS SageMaker, Azure ML |
| Azumo | OpenAI, LangChain, Hugging Face, Python, AWS |
| InData Labs | Python, PyTorch, TensorFlow, AWS SageMaker, Apache Spark |
| MobiDev | Python, PyTorch, TensorFlow, OpenCV, LangChain |
| Uvik Software | Python, Django, FastAPI, LangChain, Databricks |
| N-iX | Python, Databricks, Apache Spark, Azure ML, AWS SageMaker |
| BEON.tech | Python, AWS SageMaker, AWS Bedrock, TensorFlow, PyTorch |
| Xenoss | Python, Apache Spark, Kafka, Databricks, AWS |
| Svitla Systems | Python, AWS, Azure ML, Cloudera, React |
| Mobilunity | Python, TensorFlow, PyTorch, OpenAI, AWS |
| Vention | Python, PyTorch, TensorFlow, AWS SageMaker, Azure ML |
| Neoteric | Python, OpenAI, LangChain, React, Node.js |
| STX Next | Python, Django, PyTorch, TensorFlow, AWS |
| 10Clouds | Python, Claude, OpenAI, LangChain, AWS |
| Howdy.com | Python, AWS, Databricks, TensorFlow, Docker |
| Toptal | Python, PyTorch, TensorFlow, OpenAI, LangChain |
| Turing | Python, PyTorch, OpenAI, LangChain, Hugging Face |
| Simform | Azure ML, Azure OpenAI, Python, Kubernetes, Databricks |
| Innowise | Python, TensorFlow, Apache Spark, AWS, Azure ML |
| X-Team | Python, TensorFlow, PyTorch, Keras, Scikit-learn |
| Netguru | Python, OpenAI, LangChain, React, AWS |
| Intellias | Python, C++, PyTorch, ROS, Azure ML |
| ScienceSoft | Python, R, Azure ML, AWS SageMaker, Apache Spark |
| Andela | Python, OpenAI, LangChain, AWS, Google Cloud |
| DataArt | Python, Azure ML, AWS, Databricks, OpenAI |
| KORE1 | Python, PyTorch, TensorFlow, AWS, Azure ML |
| Revelo | Python, OpenAI, AWS, React, Node.js |
| EPAM Systems | Claude, OpenAI, Gemini, Azure ML, AWS SageMaker |
| Globant | Claude, OpenAI, Gemini, AWS, Google Cloud |
| Itransition | Azure ML, Azure OpenAI, Power Platform, Dynamics 365, Python |
| LeewayHertz | OpenAI, LangChain, ZBrain, Python, AWS |
How were these AI staffing agencies selected?
Every agency here had to clear a basic bar before it was rated. The 2026 criteria were:
- A real AI staffing offer: a team-augmentation or dedicated-engineer service that covers ML, LLM, MLOps or data roles
- Who screens candidates: engineer-led technical vetting scored higher than recruiter-only screening
- Time to the first engineer: stated timelines, checked against client reviews where any existed
- Contract terms: replacement guarantees, trial periods and how easily you can scale down
- Employment model: agencies that employ their engineers were preferred, and open freelance marketplaces were capped at four entries
Top 10 AI staffing agencies in 2026
Summaries of the ten highest-rated agencies. Each of the 33 agencies has a full review page.
1. Tensorway
Editor's pickAI and ML engineers screened by senior engineers and placed inside your sprints within one to two weeks
Tensorway is an AI engineering company founded in 2019 and based in Alicante, Spain, with more than 20 years of software engineering experience in its leadership and delivery processes. Its staff-augmentation service places ML engineers, LLM engineers, AI agent developers, MLOps engineers, computer-vision and NLP specialists, data engineers and RAG specialists directly into a client's own team, where they work in the client's Slack, Jira and repositories. Candidates are screened by senior AI engineers through a code review, a practical task in their specialization and a communication check, so the client receives a shortlist of two or three people that is already technically vetted. Tensorway handles contracts and admin; the first engineer typically starts within one to two weeks and a full squad within three to four weeks (per company website; independently unverifiable). One published case study describes a U.S. law practice, Liner Legal, cutting medical-record processing from about a week to 5–15 minutes (per company website; independently unverifiable).
Advantages
- +Candidates are screened by working AI engineers through a code review and a practical task, so your interviews can focus on team fit
- +A shortlist of two or three people usually arrives within a week of the discovery call
- +A poor fit is replaced at no cost, and the monthly commitment can be adjusted between sprints
Things to consider
- -No public rate card, so budgeting starts with a sales call
- -The bench is far smaller than the large talent networks, which matters if you need ten or more engineers at once
- -AI and ML roles only; general full-stack or QA staffing is out of scope
- -Time-zone overlap is arranged per engagement instead of guaranteed by a fixed nearshore location
Best for: Product teams adding AI engineers fast, two-week trial
2. deepsense.ai
Editor's pickWarsaw applied-AI company that lends its data scientists and ML engineers to client teams
deepsense.ai was founded in 2014 in Warsaw, Poland, and keeps a second office in Palo Alto. It is an AI-first company whose work spans generative AI, LLMs, retrieval-augmented generation, MLOps, computer vision and edge AI. Its team-augmentation offer draws on a staff of more than 100 data scientists, data engineers and software engineers, a group that includes Kaggle competition winners and PhD holders (per company website; independently unverifiable). Clutch reviewers describe engineers who integrate with in-house teams and add capacity on strategic projects.
Advantages
- +Every engineer comes from a company that has done nothing but applied AI since 2014
- +Unusually deep bench for computer vision and edge deployment
- +Can supply data engineers alongside data scientists, so the people building features also get clean data
Things to consider
- -Bench of roughly 100 people limits how many concurrent placements it can take
- -Senior research talent is priced accordingly; rates are not published
- -Better suited to multi-month engagements than one-off fractional help
Best for: Research-heavy ML problems, senior data scientists
3. BairesDev
Editor's pickNearshore firm employing thousands of Latin American engineers, including AI-augmented and ML specialists
BairesDev was founded in 2009 in Buenos Aires and lists its headquarters in San Francisco. It employs its own engineers across Latin America, with more than 4,000 on staff according to the company; LinkedIn places it in the 1,001–5,000 employee band. Its staff-augmentation service typically stands up teams in about two weeks, and a separate AI-augmented engineer option targets teams in two to four weeks (per company website; independently unverifiable). Engineers work U.S.-aligned hours, which is the main reason hiring managers in North America choose it over Eastern European firms.
Advantages
- +Can fill five or ten seats at once, which most AI specialists on this list cannot
- +Engineers are BairesDev employees, so contracts and payroll stay off your books
- +Full working-day overlap for U.S. teams
Things to consider
- -AI is one practice among many; depth varies by individual engineer
- -Heavy marketing presence can overstate how specialized any given placement will be
- -Rates are not published
Best for: U.S. companies needing several engineers in American time zones
San Francisco nearshore company placing Latin American AI engineers inside U.S. product teams
Azumo was founded in San Francisco in 2016 by former investment banker Chike Agbai, whose first client was Twitter. Its engineers are based in more than 20 Latin American countries and work U.S. hours. The company sells three formats: staff augmentation alongside an existing team, dedicated teams, and project delivery, and its recent hiring is weighted toward generative-AI, agent and forward-deployed engineering roles. Headcount estimates range from about 80 to just over 100 depending on the source.
Advantages
- +Hiring pattern shows real investment in LLM and agent engineering, beyond generic web developers
- +No long-term commitment required for augmentation seats
- +U.S. time zones and a U.S.-based management team
Things to consider
- -Headcount is modest, so very large teams may take longer to assemble
- -Public detail on how candidates are technically screened is thin
- -No published rates
Best for: Startups adding GenAI engineers on U.S. hours
Cyprus-based AI and data company that offers dedicated ML teams alongside its R&D work
InData Labs was founded in 2014 and is headquartered in Nicosia, Cyprus, with offices in Vilnius and Miami. Its services include AI research and development, generative AI, predictive analytics, computer vision, data engineering, and a dedicated-team or staff-augmentation option. Clutch lists it as a certified AWS partner with 50–249 employees. Clutch reviewers single out its data-science and ML engineering skills.
Advantages
- +AI and data are the whole business, so placed engineers come from a specialist bench
- +Combines NLP, computer vision and predictive analytics under one contract
- +AWS partnership is useful for SageMaker-based teams
Things to consider
- -Smaller bench than nearshore generalists
- -Staff augmentation is a secondary offer next to project work
- -Limited time-zone overlap with the U.S. West Coast
Best for: Data-science-heavy teams, AWS-based ML work
Kharkiv-founded engineering firm that lets you hire one or more AI engineers into your process
MobiDev was founded in 2009 in Kharkiv, Ukraine, opened its first U.S. office in Atlanta in 2011, and now runs R&D centers in Ukraine and Łódź, Poland. Its AI team-augmentation offer starts at a single full-time engineer and quotes up to two weeks to allocate someone (per company website; independently unverifiable). The company says 89% of its engineers are middle or senior level and reports more than 65 AI and ML products built, mainly for retail, hospitality, fitness and health clients. Headcount figures range from 201–500 on aggregators to 400+ on a regional IT directory.
Advantages
- +You can start with a single engineer instead of a whole squad
- +Senior-weighted bench, with a stated six-year average experience among lead AI engineers
- +Strong record in computer vision for fitness and sports products
Things to consider
- -Much of the delivery team is in Ukraine, so some buyers will want to discuss continuity planning
- -Industry focus is narrower than the large generalists
- -No published rates
Best for: Retail and fitness products, one AI engineer to start
Tallinn-based Python staff-augmentation company with an engineer-led hiring process
Uvik Software was founded in 2015 and is headquartered in Tallinn, Estonia, with a commercial office in Ipswich, UK. It places senior Python engineers, individually or in squads of about three to eight, into client teams, and its recent work leans toward data platforms, LLM features and AI agents. The company says matched profiles arrive within 48 hours and an engineer can be working within about two weeks (per company website; independently unverifiable). Its own pages give conflicting headcounts, from 50+ to 200+ engineers.
Advantages
- +Publishes a starting rate band, which few companies on this list do
- +Screening is run by engineers rather than generalist recruiters (per company website)
- +Python focus means LLM, data and backend work can sit with the same people
Things to consider
- -Python only, so mixed-stack teams need a second vendor
- -Headcount claims vary between the company's own pages
- -Less depth in computer vision than AI-first companies
Best for: Python-heavy AI products, quick shortlist
Eastern European engineering company with staff augmentation as one of three formal cooperation models
N-iX started in Lviv, Ukraine, in 2002 and now reports about 2,400 professionals across more than 25 countries in Europe and the Americas. Staff augmentation sits alongside managed teams and full-solution delivery as one of its three cooperation models, and its AI and machine-learning practice is supported by data-engineering and cloud groups. Clutch reviewers describe it as quick to scale teams and good at integrating developers into existing groups. It serves more than 80 active enterprise clients according to a 2026 company overview.
Advantages
- +Large enough to staff data, ML and platform roles from one vendor
- +Staff augmentation is a defined product with its own process
- +Delivery hubs in several EU countries help with data-residency questions
Things to consider
- -AI is one practice inside a broad software company
- -Enterprise sales process can be slow for a single-seat request
- -No public rates
Best for: Enterprises scaling data and ML teams in Europe
Buenos Aires staff-augmentation company placing senior Latin American engineers with U.S. clients
BEON.tech was founded in 2018 and is based in Buenos Aires, Argentina. It provides long-term staff augmentation with senior Latin American engineers for U.S. companies, covering AI engineering, data science, web and mobile development and QA. Its AWS Marketplace listing describes AI work with Amazon SageMaker and Bedrock. Vetting includes technical assessments, English checks and a culture-fit review, and the company claims more than 100 client partnerships (per company website; independently unverifiable).
Advantages
- +Focuses on senior engineers, which suits teams without time to mentor
- +Built for long-term placements, so turnover risk is lower than with project shops
- +AWS-native AI experience for teams already on Bedrock or SageMaker
Things to consider
- -Self-reported rankings and partnership counts are hard to verify
- -Less suited to short fractional needs
- -No published rate card
Best for: U.S. scale-ups hiring long-term LatAm AI engineers
New York AI and data-engineering company that embeds its engineers in client teams
Xenoss was founded in 2013 by ad-tech veterans led by CEO Dmitry Sverdlik and is based in New York, with offices in London and Kyiv. It describes itself as a specialized AI and data-engineering company, and Clutch places it in the 50–249 employee band. Client reviews describe staff augmentation in practice: one London ad-tech client hired Xenoss after failing to find engineers locally, and Xenoss sourced candidates from Ukraine and integrated them into the in-house team. Its background in high-throughput ad-tech systems shows in its data-engineering work.
Advantages
- +Strong on real-time data infrastructure that ML features depend on
- +Has placed engineers into UK teams that struggled to hire locally
- +Senior leadership comes from the industry it serves most
Things to consider
- -Ad-tech focus is narrower than general AI staffing
- -Mid-sized bench
- -Rates are not public
Best for: Ad-tech and high-volume data teams
Which AI staffing agency fits your hiring need?
Short answer: the number of seats and how long you need them narrow the field faster than any feature list.
| Hiring need | Recommended agency | Why | Min. engagement |
|---|---|---|---|
| First LLM or RAG engineer on a SaaS team | Tensorway | Engineer-led screening and a two-week trial before any monthly commitment | Not disclosed |
| Five or more engineers on U.S. hours | BairesDev | Employed LatAm bench large enough to fill several seats in about two weeks | Not disclosed |
| A hard modeling problem that needs a senior data scientist | deepsense.ai | AI-only company with Kaggle winners and PhDs on staff | Not disclosed |
| GenAI or agent developer for a U.S. startup | Azumo | Recent hiring centered on GenAI, agent and forward-deployed roles | Not disclosed |
| Short advisory work from a senior specialist | Toptal | Freelancers matched in about 48 hours, with a trial period | Not disclosed |
| An AI engineer on your own payroll | KORE1 | Contract-to-hire and direct-hire paths for AI roles | Not disclosed |
| Large, compliance-heavy enterprise AI program | EPAM Systems | About 62,850 staff and thousands of model-certified engineers | Not disclosed |
How do you choose an AI staffing agency?
Short answer: check who screens candidates, whether engineers are employees, and what the contract says about replacements before you compare rates.
| Criterion | Why it matters | What to check | Red flag |
|---|---|---|---|
| Who screens candidates | A recruiter can't judge whether an ML engineer's code will hold up in production | Ask who sets and reviews the technical task | "Our recruiters are technical" with no engineer named |
| Employment model | Employed engineers tend to stay longer, and their employer handles the admin | Are placed engineers employees or contractors? | Contractor status only discovered after signing |
| Time to the first engineer | An empty seat delays the roadmap week by week | Stated time from discovery call to first commit | Timelines described only as "fast" or "flexible" |
| Replacement terms | Even good agencies make bad matches | Written replacement period and who pays for the overlap | No replacement clause in the contract |
| IP and tool access | Knowledge has to stay with you when the engagement ends | Code, docs and models stored in your own repositories | Work kept on the agency's infrastructure |
| Time-zone overlap | ML work stalls when every review waits a day | Guaranteed overlapping hours per day | Overlap promised "as needed" |
What should hiring managers know about AI staffing in 2026?
Speed is the main reason companies use an agency at all. Tensorway compares its first placement in one to two weeks with three to six months to hire the same role in-house. Those are its own figures. Still, the gap matches what most hiring managers see when they recruit senior ML engineers directly, and KORE1 quotes a 17-day average for AI roles, while the nearshore firms here mostly talk about two to four weeks for a full team.
Costs are harder to compare, because so few agencies publish rates. Of the 33 agencies reviewed, only a handful show any number at all: Uvik's starting band, Neoteric's Clutch band, Mobilunity's directory band and Howdy.com's flat 15% fee. Everyone else quotes after a call. Treat a monthly rate as a starting point and ask what it covers. Recruiting, equipment, a delivery manager and the replacement guarantee are bundled very differently from one contract to the next.
Augmentation and outsourcing are different purchases. With augmentation, engineers join your standups, commit to your repositories and follow your coding standards, so what they learn stays inside your company. Outsourcing hands the agency the process and the decisions. Several large firms on this page, including EPAM, Globant and Intellias, lean toward managed delivery even when they sell individual seats. That can be exactly what you want. Just know it before you sign.
Which agencies offer part-time experts or a trial period?
Short answer: full-time dedicated engineers are standard, but only a few agencies offer fractional experts or a formal trial. Contract-to-hire is rarer still.
| Company | Contract-to-hire | Dedicated team | Full-time dedicated engineers | Managed delivery | Part-time fractional experts | Trial period |
|---|---|---|---|---|---|---|
| Tensorway | – | – | ✓ | – | ✓ | ✓ |
| deepsense.ai | – | ✓ | ✓ | ✓ | – | – |
| BairesDev | – | ✓ | ✓ | ✓ | – | – |
| Azumo | – | ✓ | ✓ | ✓ | – | – |
| InData Labs | – | ✓ | ✓ | ✓ | – | – |
| MobiDev | – | ✓ | ✓ | ✓ | – | – |
| Uvik Software | – | ✓ | ✓ | – | – | – |
| N-iX | – | ✓ | ✓ | ✓ | – | – |
| BEON.tech | – | ✓ | ✓ | – | – | – |
| Xenoss | – | ✓ | ✓ | ✓ | – | – |
| Svitla Systems | – | ✓ | ✓ | – | – | – |
| Mobilunity | – | ✓ | ✓ | – | ✓ | – |
| Vention | – | ✓ | ✓ | – | – | – |
| Neoteric | – | ✓ | – | ✓ | – | – |
| STX Next | – | ✓ | ✓ | ✓ | – | – |
| 10Clouds | – | – | ✓ | ✓ | – | – |
| Howdy.com | – | ✓ | ✓ | – | – | – |
| Toptal | – | – | ✓ | – | ✓ | ✓ |
| Turing | – | – | ✓ | ✓ | ✓ | – |
| Simform | – | ✓ | ✓ | ✓ | – | – |
| Innowise | – | ✓ | ✓ | ✓ | – | – |
| X-Team | – | ✓ | ✓ | – | – | – |
| Netguru | – | ✓ | – | ✓ | – | – |
| Intellias | – | ✓ | – | ✓ | – | – |
| ScienceSoft | – | ✓ | ✓ | ✓ | – | – |
| Andela | – | – | ✓ | – | ✓ | – |
| DataArt | – | ✓ | – | ✓ | – | – |
| KORE1 | ✓ | – | ✓ | – | – | – |
| Revelo | – | ✓ | ✓ | – | – | – |
| EPAM Systems | – | ✓ | – | ✓ | – | – |
| Globant | – | ✓ | – | ✓ | – | – |
| Itransition | – | ✓ | – | ✓ | – | – |
| LeewayHertz | – | ✓ | – | ✓ | – | – |
How much does it cost to hire an AI engineer through an agency?
Short answer: few agencies publish rates. The figures below are the only public ones we found, so expect to collect quotes.
| Hiring model | Published cost data | Time to start | Best for |
|---|---|---|---|
| Full-time dedicated engineer (agency employee) | Billed monthly. Published bands: Uvik from about $50–$99/hr; Mobilunity $25–$49/hr per a third-party directory | 1–4 weeks to start | Ongoing product work |
| Part-time fractional expert | Hourly or weekly billing; rates on request at most agencies | Days to two weeks | Reviews, architecture decisions, short sprints |
| Freelance marketplace contractor | Roughly $60 to $150+ per hour on Toptal, per third-party reports | About 48 hours to match (Toptal's own claim) | Short, well-defined specialist work |
| Nearshore hire with a published fee | Engineer's pay plus a flat 15% fee at Howdy.com | 2–4 weeks | Long-term LatAm hires with cost visibility |
| Contract-to-hire or direct hire | Contract bill rate, then a placement fee quoted by the recruiter | KORE1 cites a 17-day average | Permanent hires on your own payroll |
Which AI staffing agencies let you start with one engineer?
Short answer: MobiDev, Uvik, Mobilunity, Vention and Howdy.com all accept a single-engineer start. Agencies with stated minimums are listed first.
| Company | Minimum engagement | Best for at this budget |
|---|---|---|
| MobiDev | 1 full-time engineer | Retail and fitness products, one AI engineer to... |
| Uvik Software | 1 engineer | Python-heavy AI products, quick shortlist. |
| Mobilunity | 1 dedicated developer | Budget-conscious teams hiring a dedicated AI developer. |
| Vention | 1 developer | Startups and scale-ups wanting CVs within two days. |
| Howdy.com | 1 engineer | Teams that want transparent nearshore pricing. |
| Neoteric | $10K | Product teams adding GenAI to an existing app. |
| Tensorway | Not disclosed | Product teams adding AI engineers fast, two-week trial. |
| deepsense.ai | Not disclosed | Research-heavy ML problems, senior data scientists. |
| BairesDev | Not disclosed | U.S. companies needing several engineers in American time... |
| Azumo | Not disclosed | Startups adding GenAI engineers on U.S. hours. |
| InData Labs | Not disclosed | Data-science-heavy teams, AWS-based ML work. |
| N-iX | Not disclosed | Enterprises scaling data and ML teams in Europe. |
| BEON.tech | Not disclosed | U.S. scale-ups hiring long-term LatAm AI engineers. |
| Xenoss | Not disclosed | Ad-tech and high-volume data teams. |
| Svitla Systems | Not disclosed | Companies wanting both Mexican and Polish delivery options. |
| STX Next | Not disclosed | Python product teams adding ML capacity. |
| 10Clouds | Not disclosed | Banks, insurers and fintechs building AI features. |
| Toptal | Not disclosed | Short engagements with a senior freelance specialist. |
| Turing | Not disclosed | Companies wanting LLM-savvy contractors from a large pool. |
| Simform | Not disclosed | Azure-based companies wanting a lower-cost dedicated AI team. |
| Innowise | Not disclosed | Enterprises needing many seats filled within days. |
| X-Team | Not disclosed | Media and gaming teams adding long-term remote developers. |
| Netguru | Not disclosed | Consumer brands adding AI to digital products. |
| Intellias | Not disclosed | Automotive and mobility companies, embedded AI. |
| ScienceSoft | Not disclosed | Regulated industries hiring experienced data scientists. |
| Andela | Not disclosed | Distributed teams hiring vetted contractors worldwide. |
| DataArt | Not disclosed | Financial and travel firms needing long-lived dedicated teams. |
| KORE1 | Not disclosed | U.S. companies that want to hire AI engineers... |
| Revelo | Not disclosed | Companies hiring LatAm developers without a local entity. |
| EPAM Systems | Not disclosed | Global enterprises with large, compliance-heavy AI programs. |
| Globant | Not disclosed | Enterprises open to outcome-priced AI delivery. |
| Itransition | Not disclosed | Microsoft-stack enterprises adding AI to Dynamics or Power... |
| LeewayHertz | Not disclosed | Companies already using The Hackett Group or ZBrain. |
Which AI staffing agency is best for your industry?
Short answer: industry experience matters most where data is regulated or the domain is unusual, such as medical records, trading systems or vehicle perception.
| Industry | Recommended agency | Reason |
|---|---|---|
| Healthcare and legal | Tensorway | Medical-record processing case study for a U.S. law practice (per company website) |
| Banking and insurance | 10Clouds | AI unit dedicated to financial institutions after its 2026 merger |
| Retail, fitness and hospitality | MobiDev | More than 65 AI and ML products built for these sectors (per company website) |
| Ad tech and media | Xenoss | Founded by ad-tech veterans and strong on high-volume data systems |
| Automotive and mobility | Intellias | Named a Gartner Specialist for physical-AI services in 2026 |
| Manufacturing | deepsense.ai | Computer-vision and edge-AI depth suited to factory use cases |
Which industries does each agency staff for?
Short answer: most firms cover multiple industries. Use this table to filter by your vertical.
| Company | SaaS | Healthcare | Fintech | E-commerce | Manufacturing | Logistics |
|---|---|---|---|---|---|---|
| Tensorway | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| deepsense.ai | – | ✓ | ✓ | ✓ | ✓ | – |
| BairesDev | ✓ | ✓ | ✓ | ✓ | – | – |
| Azumo | ✓ | ✓ | ✓ | – | – | – |
| InData Labs | – | ✓ | ✓ | ✓ | – | – |
| MobiDev | – | ✓ | – | ✓ | – | – |
| Uvik Software | ✓ | – | ✓ | ✓ | – | – |
| N-iX | – | ✓ | ✓ | – | ✓ | ✓ |
| BEON.tech | ✓ | ✓ | ✓ | ✓ | – | – |
| Xenoss | – | – | ✓ | ✓ | – | – |
| Svitla Systems | ✓ | ✓ | ✓ | – | – | – |
| Mobilunity | ✓ | ✓ | ✓ | ✓ | – | – |
| Vention | ✓ | ✓ | ✓ | ✓ | – | – |
| Neoteric | ✓ | – | – | ✓ | ✓ | – |
| STX Next | ✓ | ✓ | ✓ | – | – | – |
| 10Clouds | ✓ | – | ✓ | – | – | – |
| Howdy.com | ✓ | ✓ | ✓ | ✓ | – | – |
| Toptal | ✓ | ✓ | ✓ | – | – | – |
| Turing | ✓ | ✓ | ✓ | – | – | – |
| Simform | ✓ | ✓ | ✓ | – | – | ✓ |
| Innowise | – | ✓ | ✓ | ✓ | – | ✓ |
| X-Team | – | – | ✓ | – | – | – |
| Netguru | – | – | ✓ | ✓ | – | – |
| Intellias | – | – | ✓ | – | – | ✓ |
| ScienceSoft | – | ✓ | ✓ | – | ✓ | – |
| Andela | ✓ | ✓ | ✓ | – | – | – |
| DataArt | – | ✓ | ✓ | – | – | – |
| KORE1 | ✓ | ✓ | ✓ | – | ✓ | – |
| Revelo | ✓ | – | ✓ | ✓ | – | – |
| EPAM Systems | – | ✓ | ✓ | – | ✓ | – |
| Globant | – | ✓ | ✓ | – | – | – |
| Itransition | – | ✓ | – | – | ✓ | ✓ |
| LeewayHertz | – | ✓ | ✓ | – | ✓ | – |
Which AI roles can each agency supply?
Short answer: ML engineers are easy to find; MLOps, computer vision and agent developers narrow the list quickly.
| Company | Roles and engagement options |
|---|---|
| Tensorway | ML Engineers, LLM Engineers, AI Agent Developers, MLOps, Fractional Experts, Dedicated Teams, Trial Period |
| deepsense.ai | ML Engineers, LLM Engineers, Computer Vision, MLOps, RAG & GenAI, Eastern Europe Talent |
| BairesDev | ML Engineers, Data Engineering, MLOps, Dedicated Teams, Nearshore LatAm |
| Azumo | LLM Engineers, AI Agent Developers, RAG & GenAI, Dedicated Teams, Nearshore LatAm |
| InData Labs | ML Engineers, Computer Vision, NLP, Data Engineering, Dedicated Teams, Eastern Europe Talent |
| MobiDev | ML Engineers, Computer Vision, AI Agent Developers, Dedicated Teams, Eastern Europe Talent |
| Uvik Software | LLM Engineers, AI Agent Developers, Data Engineering, Dedicated Teams, Eastern Europe Talent |
| N-iX | ML Engineers, Data Engineering, MLOps, Dedicated Teams, Eastern Europe Talent |
| BEON.tech | ML Engineers, LLM Engineers, Data Engineering, Nearshore LatAm, Dedicated Teams |
| Xenoss | Data Engineering, ML Engineers, MLOps, Dedicated Teams, Eastern Europe Talent |
| Svitla Systems | ML Engineers, Data Engineering, Dedicated Teams, Nearshore LatAm, Eastern Europe Talent |
| Mobilunity | ML Engineers, LLM Engineers, Fractional Experts, Dedicated Teams, Eastern Europe Talent |
| Vention | ML Engineers, NLP, Computer Vision, MLOps, Dedicated Teams, Eastern Europe Talent |
| Neoteric | LLM Engineers, RAG & GenAI, Dedicated Teams, Eastern Europe Talent |
| STX Next | ML Engineers, Computer Vision, Data Engineering, Dedicated Teams, Eastern Europe Talent |
| 10Clouds | LLM Engineers, AI Agent Developers, RAG & GenAI, Eastern Europe Talent |
| Howdy.com | ML Engineers, Data Engineering, Nearshore LatAm, Dedicated Teams |
| Toptal | ML Engineers, LLM Engineers, Fractional Experts, Trial Period, Talent Marketplace |
| Turing | ML Engineers, LLM Engineers, AI Agent Developers, Talent Marketplace |
| Simform | ML Engineers, AI Agent Developers, MLOps, Dedicated Teams |
| Innowise | ML Engineers, Data Engineering, Dedicated Teams, Eastern Europe Talent |
| X-Team | ML Engineers, LLM Engineers, Dedicated Teams |
| Netguru | LLM Engineers, RAG & GenAI, Dedicated Teams, Eastern Europe Talent |
| Intellias | ML Engineers, Computer Vision, AI Agent Developers, Dedicated Teams, Eastern Europe Talent |
| ScienceSoft | ML Engineers, Data Engineering, Dedicated Teams |
| Andela | ML Engineers, LLM Engineers, Talent Marketplace |
| DataArt | ML Engineers, LLM Engineers, Data Engineering, Dedicated Teams, Eastern Europe Talent |
| KORE1 | ML Engineers, LLM Engineers, MLOps |
| Revelo | LLM Engineers, Nearshore LatAm, Talent Marketplace |
| EPAM Systems | ML Engineers, LLM Engineers, MLOps, Data Engineering, Dedicated Teams, Eastern Europe Talent |
| Globant | AI Agent Developers, LLM Engineers, Dedicated Teams, Nearshore LatAm |
| Itransition | ML Engineers, Data Engineering, Dedicated Teams |
| LeewayHertz | LLM Engineers, AI Agent Developers, RAG & GenAI, Dedicated Teams |
How was this list compiled?
We started with agencies that place AI and ML engineers into client teams, then checked each one's founding year, headquarters and headcount against LinkedIn, Crunchbase, Clutch or company filings. Where sources disagreed, the profile says so. No agency paid to appear here.
Freelance marketplaces were capped at four entries (Toptal, Turing, Andela and Revelo), since this list is written for hiring managers who want engineers with an employer behind them. Companies with no visible staffing or team-augmentation offer for AI roles were dropped during research, and that removed some well-known AI consultancies.
Ratings reflect how well each agency suits a team that needs to hire AI engineers. The weighting favors screening depth, time to the first engineer, replacement and contract terms, and how much admin the agency takes off your plate. Scale still counts, which is why EPAM wins on breadth, but it doesn't outrank specialist screening. Claims we couldn't check independently are tagged on each profile.
Frequently asked questions
What does an AI staffing agency actually do?
It finds, vets and contracts AI engineers who then work inside your team, under your management. You set priorities and review the code. The agency handles recruiting, employment paperwork and payroll, and replaces the engineer if the match fails. A project outsourcing firm is a different arrangement, because it takes responsibility for delivering an outcome.
Should I use an agency or recruit AI engineers in-house?
Use an agency when the role is urgent, the specialization is hard to recruit for (speech, edge computer vision, retrieval-augmented generation (RAG), agents), or you aren't sure the role will still exist in a year. Recruit directly when you need someone permanent to own a product area for years. Contract-to-hire through a firm like KORE1 falls between the two.
Who owns the code and models an augmented engineer builds?
You should, and the contract ought to say so in plain words. Ask for written confirmation that code, documentation and trained model weights belong to your company and live in your repositories from day one. Tensorway states this on its service page, and most agencies that employ their engineers will agree when asked. On freelance marketplaces, read the IP assignment clause in the platform terms.
Can I hire a part-time AI expert instead of a full-time engineer?
Yes. Tensorway, Mobilunity and Toptal all offer part-time arrangements billed hourly or weekly. Fractional help works well for a model review, an evaluation framework or a GenAI architecture decision. It works badly when the same person is also expected to ship features every sprint.
Which AI staffing agency is best for startups?
Startups usually need one or two engineers quickly and can't absorb a bad hire. Tensorway's two-week trial sprint, Uvik's single-engineer minimum and Mobilunity's lower rate band all fit that situation. Or try Neoteric: its $10K minimum buys a small team extension to test one GenAI feature.
Compare AI staffing agencies head to head
Each comparison page provides a side-by-side analysis of two agencies across pricing, tech stack, services, and use case fit. 528 total comparison pages available.
Additional comparisons for all 33 agencies are accessible via each profile page.
Looking for an alternative to a specific agency?
Looking for alternatives to a specific agency? Each alternatives page lists ranked alternatives covering all 33 agencies in this review.