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Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Set the technical direction for ML infrastructure at Voxel
- Architect and build the training infrastructure that lets the applied ML team run multiple experiments concurrently
- Own the train-to-deploy handoff
- Pick and roll out the experiment tracking and lifecycle stack
- Establish DevOps-for-ML best practices
- Mentor engineers across Vision & AI on ML infrastructure best practices
- Anticipate where the infrastructure needs to be in 12 to 18 months
Requirements
What you’ll need- 7+ years building and shipping large-scale software systems, with at least 3 years focused on ML infrastructure or large-scale data infrastructure
- A track record of being the person who decides the architecture, not just the person who implements it
- Deep fluency in PyTorch and the modern ML training stack
- Strong Python. Performant, maintainable code that holds up in production
- A pragmatic shipping orientation
- Strong communication skills.
Benefits
Comp & perks- Equity through Voxel’s Equity Incentive Plan
- Total compensation includes base salary, annual bonus, and equity
- Comprehensive health, dental, and vision insurance
- Competitive paid parental leave
- Unlimited PTO and flexible work arrangements
- Daily meals in-office, team events, annual company onsite
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
ML infrastructurelarge-scale software systemsPyTorchPythonexperiment trackingDevOps-for-MLtraining infrastructureproduction codearchitecture designdata infrastructure
Soft Skills
communicationmentoringleadershippragmatic orientation