Hire AI engineers and AI talent for your team
Offshore Employee helps companies hire dedicated AI talent: AI-native developers, machine learning engineers, data science engineers, forward deployed engineers, AI tech leads and domain experts. Each professional is technically vetted, interviewed by you, and works as part of your team. Choose a role below, or tell us what you're building and we'll recommend the mix.
Which AI role do you need?
| Role | What they do | Hire them when you need to… |
|---|---|---|
| AI-native developer | Build product features on LLMs: prompting, RAG, agents, tool use, evals | Ship an AI feature or assistant into your product |
| ML engineer | Train, tune, deploy and monitor models on your own data | Build custom models or run ML in production reliably |
| Data science engineer | Analysis, experiments, forecasting, and the data pipelines behind them | Turn data into decisions or prepare data for AI |
| Forward deployed engineer | Embed with customers to configure, integrate and deploy your AI product | Make your AI product succeed inside customer environments |
| AI tech lead | Own architecture, standards, hiring bar and delivery for an AI team | Lead or scale an AI team, or rescue a stalled AI project |
| Domain expert | Bring industry knowledge to data, prompts, evaluation and product decisions | Make AI accurate and trustworthy in a specialist field |
AI engineer vs ML engineer vs data scientist
An AI engineer builds applications on top of existing foundation models. An ML engineer trains and operates models, usually on your own data. A data scientist analyzes data to answer business questions and design experiments.
Most AI products need the first; custom models need the second; every data-driven company needs the third.
AI talent we place
AI engineers
Hire AI-native developers who build with LLMs, RAG, agents and evals. Dedicated to your team, technically vetted, supported by us.
ML engineers
Dedicated ML and MLOps engineers who train, ship and monitor models on your data. Interview a vetted shortlist.
Data science engineers
Data science and data engineering talent that turns your data into decisions and production pipelines. Dedicated, vetted, supported.
Forward deployed engineers
Engineers who embed with your customers to deploy AI in the real world. Learn what an FDE does and how to hire one.
AI tech leads
Senior AI leads who set architecture, standards and delivery for your AI team, full-time or fractional.
Domain experts
Healthcare, finance, legal and industry experts who shape, evaluate and improve your AI products.
What every AI hire comes with
- Technical vetting by engineers before you meet them
- A shortlist, not a pile of CVs
- Works in your time zone, during your working hours
- Ongoing support from our team: HR and admin, equipment, regular check-ins and replacements
Also available
Questions, answered.
What skills should an AI engineer have in 2026?
Strong Python or TypeScript, experience with LLM APIs and open-weight models, retrieval (RAG) and vector databases, agent and tool-use frameworks, evaluation and observability, and the judgment to ship reliable features, not just demos.
Should I hire an AI engineer or an ML engineer first?
If you are building on existing models like GPT, Claude or Llama, start with an AI engineer. If your advantage depends on training models on proprietary data, start with an ML engineer.
Can you build a full AI team?
Yes. We can place a combination, for example an AI tech lead, two AI engineers and a data engineer, and grow it over time.
Your next great AI team starts here.
Tell us what you're building. We'll help you find the people to move it forward.