Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,383 postings in the last year. Stated ranges, not salaries paid.
Research Engineer, Data Infrastructure
Palo Alto, California, United States
Actively hiring, first seen by us today- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: FullTime
From the employer’s posting
What you’ll work on
Full postingBuild & Scale: Help us reach our goal of operating massive distributed compute and storage systems
From the employer’s posting
What You Will Do Build & Scale: Help us reach our goal of operating massive distributed compute and storage systems Global Orchestration: Architect and maintain multi-cluster orchestration layers to optimize workload placement across diverse hardware and regions. • Design Future-Proof Storage: Architect our transition to modern storage formats to handle fine-tuning datasets at a scale that anticipates exabyte growth. • Platform Engineering: Contribute to the development of our internal training platform, ensuring seamless model training and fine-tuning capabilities across Kubernetes and SLURM based environments. • Metadata & Lineage: Implement and manage systems to provide clear visibility and lineage as our data and model pipelines grow in complexity. • Operational Excellence: Use modern deployment workflows to manage cloud-native deployments, ensuring our data platform can scale by orders of magnitude while remaining reliable and efficient.
Benefits in the posting
Full benefits wording- We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
- Privacy Policy
From the employer’s posting.
About mistral.ai
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 9, 2026today
- Recorded sightings
- 1
- Employer says posted
- Jul 10, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 0
Early. Similar jobs usually come down between day 7 and day 72.
From 4,777 similar postings that came down. Coming down is not always a hire.
mistral.ai is hiring
18 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- Kubernetes
Where the posting names them
What We're Looking For • Have 4+ years of experience in Data Infrastructure, MLOps, or Infrastructure Engineering. • Have experience or a strong interest in supporting foundational compute and storage platforms. • Are proficient in Python and enjoy solving the "brittle data lake" problem with modern, columnar storage standards. • Are well-versed in Kubernetes-native tooling and excited to debug large-scale distributed systems across multi-cluster environments. • Take pride in building and operating scalable, reliable, and secure systems from the ground up. • Are comfortable with ambiguity and the challenges of building high-scale infrastructure in a rapid-growth AI environment. What We Offer
• Build & Scale: Help us reach our goal of operating massive distributed compute and storage systems • Global Orchestration: Architect and maintain multi-cluster orchestration layers to optimize workload placement across diverse hardware and regions. • Design Future-Proof Storage: Architect our transition to modern storage formats to handle fine-tuning datasets at a scale that anticipates exabyte growth. • Platform Engineering: Contribute to the development of our internal training platform, ensuring seamless model training and fine-tuning capabilities across Kubernetes and SLURM based environments. • Metadata & Lineage: Implement and manage systems to provide clear visibility and lineage as our data and model pipelines grow in complexity. • Operational Excellence: Use modern deployment workflows to manage cloud-native deployments, ensuring our data platform can scale by orders of magnitude while remaining reliable and efficient. What We're Looking For
Your next step
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
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- No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.
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Has mistral.ai posted this job before?
Yes. We’ve followed one other Research Engineer, Data Infrastructure job there since November 2026. It is still up.
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 13% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
About Mistral
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.
We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
The Role
This role focuses on building and operating the next generation of data infrastructure at Mistral AI. You will be a core contributor to our evolution, helping us design and scale massive compute fleets and storage systems designed for high performance and scalability.
You will help us move toward a future of decoupled control and data planes, scaling big data compute and storage platforms while ensuring secure and governed data access for MLOps and research. You will take full lifecycle ownership: from architecting the migration away from legacy orchestrators to implementing production-grade pipelines and participating in on-call rotations for critical training jobs.
What You Will Do
• Build & Scale: Help us reach our goal of operating massive distributed compute and storage systems
• Global Orchestration: Architect and maintain multi-cluster orchestration layers to optimize workload placement across diverse hardware and regions.
• Design Future-Proof Storage: Architect our transition to modern storage formats to handle fine-tuning datasets at a scale that anticipates exabyte growth.
• Platform Engineering: Contribute to the development of our internal training platform, ensuring seamless model training and fine-tuning capabilities across Kubernetes and SLURM based environments.
• Metadata & Lineage: Implement and manage systems to provide clear visibility and lineage as our data and model pipelines grow in complexity.
• Operational Excellence: Use modern deployment workflows to manage cloud-native deployments, ensuring our data platform can scale by orders of magnitude while remaining reliable and efficient.
What We're Looking For
• Have 4+ years of experience in Data Infrastructure, MLOps, or Infrastructure Engineering.
• Have experience or a strong interest in supporting foundational compute and storage platforms.
• Are proficient in Python and enjoy solving the "brittle data lake" problem with modern, columnar storage standards.
• Are well-versed in Kubernetes-native tooling and excited to debug large-scale distributed systems across multi-cluster environments.
• Take pride in building and operating scalable, reliable, and secure systems from the ground up.
• Are comfortable with ambiguity and the challenges of building high-scale infrastructure in a rapid-growth AI environment.
What We Offer
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page.
Privacy Policy
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Palo Alto, California, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.