Staff Research Engineer, Scientific Computing and ML/Physics Infrastructure
Cambridge, MA USA; London, UK; San Francisco, CA USA
USD 224K-294K Senior-level Full Time
Tasks
- Architect job orchestration retry monitoring and workflow traceability
- Build ML and physics infrastructure for model training and simulation workflows
- Debug code environments infrastructure and data pipelines
- Document systems and establish engineering patterns for research teams
- Ensure workflows run reliably across clusters
- Improve GPU utilization and distributed execution
- Maintain reproducible local cloud and GPU environments
- Optimize performance for ML physics and pipeline code
- Package scientific tools into reusable services workflows or APIs
- Scale research tools into production systems
Perks/Benefits
- N/A
Skills/Tech-stack
API Development | Argo | CUDA | Checkpointing | Containerization | Data Processing | Distributed Systems | Distributed execution | Docker | Failure analysis | Fault Tolerance | Flyte | GPU Computing | JAX | Kubernetes | Linux | Monitoring | Performance Profiling | PyTorch | Python | Ray | Reproducibility | Slurm | Workflow Orchestration
Education
N/A
Roles
Regions
Countries
States
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