Research Engineer, ML Platform
Mistral AI · Palo Alto
CHECKED 10H AGO
Frontier labremotesenior
At a glance
Highlights
- Build ML platform powering large-scale training, evaluation and batch inference.
- Orchestrate GPU workloads with queueing, admission control and smart placement.
- Enable multi-cluster execution based on capacity, data locality and hardware needs.
What they offer
- Healthcare coverage
- Parental leave
- Retirement plans
- Relocation support
- Wellness programs
- Meal and transportation allowances
Ideal candidate
A platform-minded engineer with ML infrastructure experience who loves simplifying complex systems and improving researcher experience, thriving in ambiguous, fast-moving frontier AI research environments.
Requirements
- 4+ years of experience in ML infrastructure, distributed systems, Kubernetes platform engineering, or a related field
- Proficient in Python or Go and comfortable with production-grade distributed systems
- Strong Kubernetes knowledge including controllers, operators, CRDs, scheduling, networking and storage
- Understand distributed ML workloads including training, fine-tuning, evaluation and batch inference
- Familiar with GPU infrastructure including PyTorch, CUDA, NCCL and high-performance networking
- Understand quotas, priorities, preemption, gang scheduling, topology awareness and admission
- Can diagnose performance and reliability problems across software, orchestration and hardware
- Care about developer experience and turning complex infrastructure into simple interfaces
- Thrive in ambiguous, fast-moving environment shaped by frontier AI research
Lab profile
About Mistral AI
Provides full-stack AI solutions from frontier models to tools, applications, and compute.
What they build
- Frontier AI models
- Developer tools
- AI applications
Known for
- Full-stack AI development
- Enterprise co-creation and deployment
- Customizable systems that run on customer terms
- Focus on finance, manufacturing, defense, healthcare and public sector