AI Research Engineer

Our client is an AI safety startup building the safety, reliability, and optimization layer for advanced AI systems. At the heart of the platform are natural-language policies—rules that clearly define what an AI model should and shouldn’t do. These policies are automatically tested, enforced, and continuously improved at scale.

The company has raised $11M from leading funds as well as founders and senior leaders from major AI labs and technology companies.

Its systems handle hundreds of millions of API calls every month, and the team fine-tunes and trains proprietary LLMs that run faster and more cost-effectively than both open-source and commercial alternatives.

This is a small, highly focused team where you’ll work on complex problems, ship to production quickly, and directly shape how AI safety is implemented in real systems.

What You’ll Do

• Train LLMs and VLMs using distributed training frameworks (e.g., Megatron, DeepSpeed).
• Design and implement Mixture-of-Experts architectures for high-efficiency scaling.
• Build multimodal training pipelines handling text, images, and audio.
• Develop custom Triton kernels to optimize training bottlenecks.
• Explore new architectures, hyperparameter strategies, and dataset compositions.

You’re a Great Fit If You

• Have experience fine-tuning large models.
• Understand distributed training deeply: tensor parallelism, pipeline parallelism, expert parallelism, ZeRO, FSDP.
• Can write Triton kernels to accelerate attention, MLP layers, or custom operators.
• Have worked with multimodal systems (e.g., Llava-style, Flamingo-style).
• Care about training stability, convergence, and maximizing hardware throughput.

Compensation & Benefits

• Competitive salary plus stock options
• 20 days paid vacation
• Hybrid work from Paris with relocation support
• Top-tier medical insurance
• All the hardware, tools, and services needed for your role
• Paid subscriptions for AI agents and developer tools
• Twice-yearly team off-sites (recent trips included the Alps and Saint-Tropez)

Hiring Process

1. Introductory call with a team member
2. Technical interview
3. (Optional) Take-home assignment
4. Final conversation with executive leadership