Mistral AI

Research Engineer, Machine Learning

Mistral AI
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2 months ago
Palo Alto, CA, USA or San Francisco, CA, USAMid Level

Responsibilities

  • Build and optimize large-scale machine learning pipelines and robust research tools.
  • Enhance shared training frameworks, data pipelines, and cluster tooling or embed within research squads to turn research ideas into scalable code.
  • Integrate checkpoints, streamline evaluation, and expose APIs connecting research systems to production.
  • Conduct deep-learning experiments involving sparsified large models and distributed training across thousands of GPUs.
  • Design, implement, and benchmark ML algorithms in efficient Python code.
  • Deliver prototypes that become production-grade components for Le Chat and the enterprise API.

Requirements

  • Master’s or PhD in Computer Science, or an equivalent proven track record.
  • At least 4 years of experience working on large-scale ML codebases.
  • Hands-on experience with PyTorch, JAX, or TensorFlow and distributed training using technologies such as DeepSpeed, FSDP, SLURM, or Kubernetes.
  • Experience in deep learning, NLP, or LLMs.
  • CUDA or data-pipeline experience is a bonus.
  • Strong software-design skills, including testing, code review, and CI/CD.
  • Self-starter who is collaborative, low-ego, and team-oriented.

Benefits

  • Benefits may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal allowances, transportation allowances, and other location-specific perks.
  • Benefits vary by country and location.

Tech Stack

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Mistral AI

About Mistral AI

1,001-5,000 employees

Mistral AI builds foundation language models and full‑stack AI solutions for enterprises, offering APIs, on‑prem deployment, developer tools, and applications. The privately held company, founded in 2023 and headquartered in Paris, partners with organizations in finance, manufacturing, defense, healthcare, and the public sector to co‑create customized systems. It releases open‑source models alongside commercial offerings and makes its models available through major cloud marketplaces.

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