Applied Scientist: Multi-Modality AI & Deployment

Mistral Ai; Palo Alto (CA); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Mistral AI seeks Applied Scientists and Research Engineers to drive innovative research and collaborate with clients on complex projects. You will develop SOTA models across text, image, and speech, applying novel methods to real use cases with cross-functional teams.

You will work across data generation, model training, evaluation, and deployment, tackle challenging problems with agents and RAG pipelines, and communicate progress to client research teams.

Qualifications

• Excellent communication skills to explain complex ideas to diverse audiences.
• Expert in PyTorch or JAX.
• Able to contribute to large codebases with minimal guidance.
• Writes clean, high-performance Python code.
• Self-driven: you just ship, with no need for roadmaps or managers.
• Low-ego, collaborative and eager to learn.
• Track record of success via personal or academic projects.

Responsibilities

• Run pre-training, post-training and deploy state-of-the-art models on clusters with thousands of GPUs.
• Generate and curate data for pre-training and post-training, including evaluations to beat performance targets.
• Develop tools and frameworks to facilitate data generation, model training, evaluation and deployment.
• Collaborate with cross-functional teams to tackle complex use cases using agents and RAG pipelines.
• Manage research projects and communications with client research teams.

Skills

PyTorch

JAX

Python

Independent thinker

Communication skills

Team collaboration

Education

PhD or Master's in ML/CS/Math/Physics

Job description

Mistral AI seeks Applied Scientists and Research Engineers to drive innovative research and collaborate with clients on complex projects. You will develop SOTA models across text, image, and speech, applying novel methods to real use cases with cross-functional teams.

You will work across data generation, model training, evaluation, and deployment, tackle challenging problems with agents and RAG pipelines, and communicate progress to client research teams.