Research Engineer: AI Training & Deployment Pipelines

Mistral; Paris; Presencial; EUR 90.000 - 140.000; Jornada completa

Descripción de la vacante

Mistral on Forge develops end-to-end training and deployment workflows for client AI solutions. You will work across CPT/SFT/RL/distillation, evaluation, data, and infrastructure to turn prototypes into reliable production pipelines.

You will collaborate with scientists, engineers, product, and customer-facing teams to ensure Forge projects ship, are maintainable, and trusted by others. Interview focus varies across algorithms, infra, evals, or data.

Formación

• Strong Python engineering skills and experience working in large codebases.
• Hands-on experience with PyTorch, JAX, or similar.
• Strong systems and infrastructure fundamentals.
• Experience with LLM training or post-training: fine-tuning, RL, distillation, evaluation, and/or data pipelines.
• Excellent debugging skills in ambiguous systems (distributed jobs, data issues, quality regressions, infra failures).
• Clear communication with technical and non-technical stakeholders.
• High agency, low ego, and comfort in fast-moving, under-specified environments.

Responsabilidades

• Build and improve post-training and evaluation workflows (CPT/SFT/RL/distillation), turning prototypes into repeatable Forge “recipes”.
• Develop tools and pipelines for synthetic data generation, data curation, training, evaluation, and deployment.
• Debug and harden large-scale ML systems: distributed training, scheduling/execution, checkpointing, observability, and reproducibility.
• Improve the Forge codebase via clear APIs, tests, documentation, and maintainable abstractions.
• Push the frontier of our RL training stack (e.g., high-throughput async rollout and scalable post-training systems at frontier-model scale).
• Make sure Forge deployment is seamless and adaptable to a diversity of clients (hardware access, software stack, cloud and on-premises, …).
• Partner with researchers and infrastructure engineers to translate bottlenecks into concrete system improvements.

Conocimientos

Python

Distributed systems

Debugging

Communication

Adaptability

Herramientas

PyTorch

JAX

CUDA

Descripción del empleo

Mistral on Forge develops end-to-end training and deployment workflows for client AI solutions. You will work across CPT/SFT/RL/distillation, evaluation, data, and infrastructure to turn prototypes into reliable production pipelines.

You will collaborate with scientists, engineers, product, and customer-facing teams to ensure Forge projects ship, are maintainable, and trusted by others. Interview focus varies across algorithms, infra, evals, or data.