Hybrid Applied Scientist – Edge Devices, Quantization

at Mistral AI

• Job title: Applied Scientist – Edge Devices, Quantization
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: Open Source, Python, PyTorch
• Location requirements: Hybrid, Paris, France

About the role

• Applied Scientist/Research Engineer building efficient models for edge devices at Mistral AI. Engaging in innovative AI solutions and research projects across various device platforms.

Responsibilities

• Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs.
• Design and evaluate quantization, pruning, distillation, and sparsity methods for LLMs and multimodal models.
• Build deployment stacks, optimize kernels and memory layouts.
• Run large‑scale experiments to balance accuracy, latency, throughput, and power under tight memory constraints; profile and fix bandwidth/compute bottlenecks.
• Develop tooling for calibration data generation, mixed‑precision training, quant‑aware finetuning, structured/unstructured sparsity, and compilation passes.
• Manage research projects and communications with client research teams.

Requirements

• You are fluent in English, and have excellent communication skills.
• You’re not afraid of contributing to a big codebase and can find yourself around independently with little guidance.
• You’ve a deep understanding of quantization trade‑offs, hardware constraints, and compiler stacks
• You’re expert with PyTorch or JAX; strong C++/CUDA or low‑level performance skills a plus; production‑grade Python.
• You don’t need roadmaps: you just do. You don’t need a manager: you just ship.
• Low-ego, collaborative and eager to learn.
• You have a track record of success through personal projects, professional projects or in academia.
• It would be great if you hold a PhD / master in a relevant field (e.g., Mathematics, Physics, Machine Learning), but if you’re an exceptional candidate from a different background, you should apply.
• Have contributed to a large codebase used by many (open source or in the industry).
• Have a track record of publications in top academic journals or conferences.
• Contributions to open‑source inference/compilers stacks.
• Love improving existing code by fixing typing issues, adding tests and improving CI pipelines.
• Have experience optimizing inference on edge devices

Benefits

• 💰 Competitive cash salary and equity
• 🥕 Food : Daily lunch vouchers
• 🥎 Sport : Monthly contribution to a Gympass subscription
• 🚴 Transportation : Monthly contribution to a mobility pass
• 🧑‍⚕️ Health : Full health insurance for you and your family
• 🍼 Parental : Generous parental leave policy
• 🌎 Visa sponsorship
• 💰 Competitive cash salary and equity
• 🚑 Insurance
• 🚴 Transportation: Reimburse office parking charges, or 90GBP/month for public transport
• 🥎 Sport: 90GBP/month reimbursement for gym membership
• 🥕 Meal voucher: £200 monthly allowance for its meals
• 💰 Pension plan: SmartPension (percentages are 5% Employee & 3% Employer)