Senior Software Engineer ML Infrastructure
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Summary
Senior engineer designing distributed cloud GPU training infrastructure and building end-to-end machine-learning pipelines that plug into product workflows, while promoting ML engineering practices across the company. Focus areas include distributed GPU training, cloud infrastructure, and ML training/evaluation/deployment platforms.
You will design and implement distributed cloud GPU training for deep-learning training and evaluation. You will build end-to-end machine-learning pipelines, integrate them into product workflows, promote ML engineering practices, and collaborate across the company to solve data problems at scale.
Responsibilities
- Design and implement distributed cloud GPU training approaches
- Build end-to-end machine-learning pipelines
- Integrate machine-learning pipelines into core product workflows
- Promote ML engineering best practices
- Collaborate across the company to solve data problems at scale
Requirements
- Bachelor's degree in Computer Science, Software Engineering, or equivalent
- 3+ years of professional experience
- Experience building software components for production full-stack machine-learning challenges
- Knowledge of ML training, evaluation, and deployment platforms
- Knowledge of when to use open source versus building in-house
- Analysis
- problem-solving
Benefits
- Equity
- Health insurance
- Dental insurance
- Vision insurance
- Life insurance
- Disability insurance
- 401k retirement benefits with employer match
- Learning stipend
- Wellness stipend
- Paid time off