Job Description
A Staff Software Engineer specializing in ML infrastructure, focusing on optimizing training efficiency and input pipelines for self-driving model development, enabling faster and more reliable autonomous vehicle technology.
Key Responsibilities
- Collaborate with ML practitioners and infrastructure teams to integrate optimized input pipelines into workflows
- Detect, diagnose, and resolve performance bottlenecks in training, evaluation, and model distillation workflows
- Optimize training performance and resource utilization for consistent, reproducible model training outcomes
- Enhance input data pipelines to maximize runtime goodput and minimize accelerator idle time
- Champion best practices for robust, reproducible, and debuggable ML experimentation
Requirements
- A B.S., M.S., or Ph.D. in Computer Science, Electrical Engineering, or related technical field or equivalent experience.
- At least 4 years of professional experience in ML infrastructure, distributed training, or ML systems engineering, scaling models on multi-node, multi-accelerator clusters.
- Understanding of training, evaluation, and distillation workflows for billion-parameter models.
- Expert-level knowledge in distributed systems and remote Python.
- Strong skills in profiling, debugging, and optimizing quantized workloads.
- Experience with ML compilers and strategies to reduce startup overhead.
- Familiarity with model distillation and efficient inference workflows.
- Ability to collaborate with ML practitioners and infrastructure teams to understand needs and integrate optimized input pipelines into workflows.
- Ability to detect, diagnose, and resolve performance bottlenecks across training, evaluation, and model distillation workflows.
- Ability to optimize training performance, resource utilization, and ensure consistent, reproducible model training outcomes.
- Ability to optimize input data pipelines to increase runtime goodput, ensuring accelerators maximize their time on task and minimize idle cycles.
- Championing best practices for robust, reproducible, and debuggable ML experimentation.
Benefits & Perks
Compensation/salary range between $235,030 and $352,290 depending on experience and qualifications
Annual performance bonus
Equity in the company
Competitive benefits package
Ready to Apply?
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