Mistral AI
AI Scientist - Palo Alto
Palo Alto
Sponsorship not specifiedDetected 880 days ago
PythonJavaGoRustDistributed SystemsKubernetesMachine LearningPyTorchNLPLLMsMLOpsResearchMentoring
Stay score
odds of building a lasting career here
40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Files H-1B transfers
17 transfer filings in the last year, covering 17 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- Our diverse workforce thrives in competitive environments and is committed to driving innovation, with teams distributed between Europe, the USA and Asia.
- All while releasing frontier models open-source, for everyone to try and benefit.
- Mistral is hiring experts in the training of large language models and distributed systems.
Responsibilities
- Research and develop novel methods to push the frontier of large language models
- Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale
- This means being able to design complex software and make it usable in production
Requirements
- You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)
- You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)
- You have high engineering competence.
- You are a self-starter, autonomous and a team player
- You have hands-on experience with training large transformer models in a distributed fashion
- You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment
- You have a strong publication record in a relevant scientific domain
- Please consider applying if you believe you have the skills to contribute to Mistral's mission.
Compensation
- 💰 Competitive salary and bonus structure
Benefits
- 💰 Competitive salary and bonus structure
- 🚀 Generous Equity
- 🧑⚕️ Health: Competitive Healthcare program (Medical Provider: Blueshield of California 100% coverage for employee, 75% for dependents)
- 👴🏻 Pension: 401K (6% matching)
- 🏝️ PTO: 18 days
- 🏀 Sport: $120/month reimbursement for gym membership
- 🥕 Meal stipend: $400 monthly allowance for meals (solution might evolve as we grow bigger)
Company info
- About Mistral At Mistral we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.
- We are a dynamic, collaborative team passionate about AI and its potential to transform society.
- We are creative, low-ego and team-spirited.
- At Mistral we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.
- At Mistral, we develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives.
- Join us to be part of a pioneering company shaping the future of AI.
- 🤝 Coaching: we offer Betterup coaching on a voluntary basis
Visa & Work Authorization
- 🪪 Visa sponsorship
Apply directly at Mistral AI →Create a free account for alerts like thisView Mistral AI immigration profile
This listing is sourced directly from Mistral AI's careers page and normalized into a canonical job model.