AI Researcher
Advances the state of the art: new architectures, training methods, evaluation — and turns research into product advantage.
Why this hire matters.
Hiring an AI researcher only makes sense if your competitive edge depends on capabilities the market doesn't sell yet: proprietary models, specific training methods, frontier performance on your domain. In that case it's an existential hire — the talent war is global, waged by labs paying hundreds of thousands of dollars, and a single exceptional researcher can define your differentiation for years. In every other case it's an expensive category error: an excellent AI engineer exploiting existing models will create more value, faster. The hiring criterion beyond publications: the ability to steer research toward impact — 'product-aware' researchers are rare and worth their price. The Paris ecosystem (Mistral, Kyutai, FAIR, DeepMind Paris) makes this pool accessible but fiercely contested.
Key missions.
- Conduct research aligned with product strategy
- Design and train models (pre-training, post-training, RL)
- Build evaluation protocols and benchmarks
- Publish and represent the company in the scientific community
- Transfer research to engineering teams
- Mentor PhD students and junior researchers
- Track frontier advances
Skills.
Technical skills
- Advanced deep learning (transformers, RL, post-training)
- PyTorch/JAX and distributed compute (multi-GPU)
- Experimental methodology and evaluation
- NeurIPS/ICML/ICLR-level publications
Expected qualities
- Scientific creativity
- Perseverance
- Communicating results
- Impact orientation
Common stack
Salaries 2025-2026
| Level | Experience | Annual gross base |
|---|---|---|
| Junior (post-PhD) | 0-2 yrs | 55–75 k€ |
| Mid-level | 2-5 yrs | 70–100 k€ |
| Senior | 5-8 yrs | 90–130 k€ |
| Principal / Research Lead | 8+ yrs | 130–200 k€ |
Paris market ranges, 2025-2026.
Outside the Paris region, expect 10 to 15 % less.
Sources : Silkhom 2026 (moyenne 86 800 €) · Get in Talent 2026 · Glassdoor France 2026
Hiring this profile.
Typical background
PhD in machine learning or adjacent field in the vast majority of cases, with top-tier publications. Exceptional atypical profiles exist but remain rare.
When to hire
Only if the model IS the product or a scientific lock blocks your differentiation — labs, deep tech, ambitious AI-natives. Otherwise, prefer an AI engineer.
Career path
Senior → Research Lead / Principal Scientist → Chief AI Officer, or lab/AI-startup founder.