Recruitment agency forAI
Machine Learning Engineer, AI Engineer, Generalist AI Engineer, ML Researcher, MLOps Engineer, GenAI Engineer, Head of AI…
The best AI candidates don’t apply for jobs. We approach them directly.
0 trial periods ended early in 2025
- 37
AI hires since 2023
- 80,000+
candidates in our network
- 90%
of candidates accept our clients’ offers
Our approach
Why trust us with your AI hiring
Targeted search
We approach the best AI candidates directly through our LinkedIn Recruiter license, our talent pool and referrals. We select each candidate for their track record, their expertise and their fit with your context.
Our sourcing channels
Assessment
We build a clear scorecard with you based on your AI needs. We verify every figure a candidate cites before we present them, and we complete the assessment with structured interviews and thorough reference checks.
Sample AI scorecard
Long-term partnership
We share our market insights (salary grids, trends, signs that people are ready to move) and our search reports to help you build a strong AI team over time.
What we deliver
Tailored search report
Up-to-date salary benchmark
Tracking of candidates open to a move
Closing and onboarding follow-up
Our process
6 steps to hire the right person
Role definition and scorecard
Targeting and search strategy
Screening and assessment
Candidate presentation and reports
Support through to the signed offer
KPI review and continuous improvement
Role definition and scorecard
Targeting and search strategy
Screening and assessment
Candidate presentation and reports
Support through to the signed offer
KPI review and continuous improvement
Our AI expertise
Roles we cover, stacks we know, salary ranges and seniority levels.
AI Engineer
Builds LLMs into products: RAG, agents, tool calling and evaluation of response quality.
Machine Learning Engineer
Takes machine learning models to production: training pipelines, deployment, monitoring and retraining.
MLOps Engineer
Builds the tooling used to deploy and monitor models: feature store, model registry, serving and alerts.
Research Scientist
Advances the state of the art in machine learning in a research lab or an applied research team.
Head of AI
Sets a company’s AI strategy, leads the team and decides between off-the-shelf models and in-house development.
AI Product Manager
Chooses which AI use cases to build, defines quality metrics and manages the risks for users.
Data Scientist
Builds predictive and classification models on company data before they go into production.
Companies that trust us with AI hiring
A dedicated expert, client testimonials and completed hires to back it up.
AI client testimonials
Donia Gharbi
Founding Chief of Staff · Davis
« Lity really took the time to understand what we were looking for, and also to understand our tech, our processes, our business and our culture. Their attentiveness, their responsiveness and the quality of the candidates they sent make Lity by far our best experience with a recruitment firm. Thanks again! »
Related AI case studies
Your AI recruitment consultant
5+ years recruiting AI talent
Hiring for AI roles in France in 2026 is still difficult. The best candidates are currently employed, regularly approached by recruiters and never look at public job postings. Without a direct network and without confidentiality, a search can take several months.
Julie leads the AI practice at Lity and works with founders, executive committees and HR directors on AI searches, with detailed knowledge of the market, compensation packages and career paths.
Learn more about our approachShow less
In AI, we have worked with many kinds of companies: early-stage startups, Series A to D scale-ups, established mid-market companies and large groups going through a transformation. When the search is run in-house, the hardest profiles stay unfilled for months.
Julie knows the companies in the AI market, the actual salary ranges by seniority and company size, and the signs that a candidate is ready to leave. The team knows how to calibrate a junior, mid-level or senior hire, and checks the figures candidates quote before presenting them.
Our method relies on 4 complementary sources. Our LinkedIn Recruiter license for direct outreach to currently employed candidates. Our pool of AI candidates, which we keep up to date. Referrals from our network of top performers. And our presence at AI community events. The scorecard is built with you. For actual timelines and results, our case studies document each search.
We work with companies of every size
Startup, scale-up, SME or large enterprise: we adapt our methods to your stage of growth and your hiring needs.
Startup
1 to 30 employees
At an early-stage AI startup, you hire a highly versatile founding AI engineer who can prototype, deploy and monitor a complete GenAI system.
Scale-up
30 to 300 employees
At a scale-up, the team gets organized: an AI engineering lead, specialized ML engineers (NLP, CV) and an MLOps engineer to run deployments at scale.
SME
50 to 500 employees
In the expansion stage, the AI team grows to 15 to 30 people, with applied research, an applied team and a dedicated AI product management function.
Large companies
Mid-market companies and large groups
In a large corporation, the priorities are running AI at scale (MLOps, governance, AI Act compliance) and internal adoption through copilots for business teams.
Further reading
Resources and other Lity practices.
Other Lity practices
All our recruitment practicesRelated
Keep exploring
- Hiring in FranceContracts, salaries and notice periods for US and UK companies.
- Salaries in FranceGross, net and employer cost by role, in euros, dollars and pounds.
- Freelance recruitmentFreelance experts, available within 7 days.
- Permanent recruitmentPermanent hires in France and Europe, paid on success.
Answers to your questions about recruiting in AI.
What do AI roles pay in France in 2026?
Here are the pay ranges we see for AI roles in France in 2026:
- Mid-level generalist AI engineer: €62-78K
- Mid-level machine learning engineer: €62-78K
- Mid-level AI engineer: €70-85K
- Senior AI engineer: €85-108K
- Mid-level GenAI engineer: €78-98K
- Mid-level LLM engineer: €90-115K
- Head of AI at a scale-up: €115-138K
Some profiles fall outside the usual salary bands:
- Former Mistral, Anthropic and OpenAI employees: €150-250K + equity, in line with US standards.
- Alumni of research labs in France (Naver, FAIR, INRIA): premium packages as well.
AI, machine learning, GenAI: where are the boundaries in 2026?
AI (artificial intelligence) is the broad term. It covers:
- classic ML
- deep learning
- NLP
- computer vision
- generative AI (LLMs)
Within it, we distinguish:
- Machine learning: the original subset, based on statistical models (scikit-learn, XGBoost).
- GenAI (generative AI): focused on LLMs, RAG, agents, fine-tuning and prompt engineering.
At early-stage AI startups, the distinction matters less, because people cover several areas.
At scale-ups, roles specialize:
- ML Engineer: classic models.
- AI Engineer: LLMs and agents.
- Research Scientist: fundamental research.
How do you assess an AI candidate in an interview?
We assess AI candidates in interviews on four areas:
- Theory: ML algorithms, deep learning fundamentals, LLM internals.
- Hands-on stack: PyTorch, scikit-learn, Hugging Face, LangChain, vector databases.
- Practical test: a GenAI exercise (RAG, fine-tuning, eval) or a classic ML exercise.
- Production: ability to deploy a model, handle monitoring, and optimize latency and cost.
A strong AI candidate talks about production, evals and business trade-offs, not only state-of-the-art papers.
Mistral, Hugging Face, Naver Labs: why are their alumni so sought after?
These organizations attract candidates because they bring together top experts in their fields:
- Mistral AI (Paris): the French reference for open-weight LLMs. Every AI scale-up tries to hire its people.
- Hugging Face (NYC + Paris): the global leader in open source AI libraries.
- Naver Labs Europe (Grenoble): fundamental research in NLP and computer vision.
- FAIR (Meta AI Research): Yann LeCun’s lab, focused on fundamental research.
Former employees of these organizations get the best offers at French and international AI scale-ups (€250-400K + equity).
Is the French AI job market strong in 2026?
The French AI job market is very strong in 2026.
Every SaaS scale-up now hires 1 to 3 AI profiles to build GenAI into its product, and AI engineers and LLM engineers are the most sought after.
France is building a strong AI ecosystem, with companies such as Mistral, Hugging Face, Poolside, Dust, Hellsource, Owkin and Iliad AI Lab. On the funding side, French VC funds (Index, Iconiq, Sequoia France) invest heavily in AI startups.
Candidates returning to Europe from research labs and Big Tech get premium packages. Moving from data scientist to AI engineer is still the most common transition.
What career paths are open to AI professionals?
The typical career path looks like this:
Data Scientist or ML Engineer → AI Engineer → Senior AI Engineer → Lead AI Engineer → Head of AI
Several specializations are in high demand:
- LLM Engineer
- GenAI Engineer
- Research Scientist (PhD)
- Applied Scientist
- AI Product Manager
Other interesting moves:
- Founding AI Engineer at a pre-seed startup (with equity)
- Forward Deployed Engineer (AI plus customer-facing work)
- AI FDE
Many senior AI engineers move to freelancing (daily rate of €1000-1500) or join labs (Mistral, OpenAI, Anthropic) as remote employees.
Trust us with your hiring in AI.
A hands-on approach for hires that last.
Intro call (30 min)
A video call to understand your needs and walk you through our approach.
On-site visit
We meet you on site to get a detailed understanding of your culture and your hiring plans.
Targeted search
The search starts. We present only the candidates who match your requirements.