Principal Software Lead, Machine Learning
Standard Bots
full-time
Posted on:
Location Type: Hybrid
Location: New York City • California • New York • United States
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Salary
💰 $250,000 - $300,000 per year
Job Level
About the role
- Design and implement state of the art ML models and training pipelines
- Apply novel machine learning techniques to a wide range of robotics applications
- Develop efficient data and training strategies
- Implement model evaluation frameworks and metrics tracking
- Lead model development and iteration with focus on rapid experimentation and prototyping of new model architectures
- Performance optimization and model debugging
- Transfer learning and fine-tuning strategies
- Build robust evaluation and debugging systems to analyze model behavior and failure modes
- Implement interpretability tools and visualization frameworks
- Track and improve model metrics
- Collaborate with engineering team to optimize training infrastructure and deployment
Requirements
- 5+ years of AI modeling experience, specifically within the self-driving car industry (or PhD with 3+ years of AI modeling experience in the self-driving car industry)
- Proven track record developing and deploying large-scale ML models
- Experience using the latest techniques in diffusion and autoregressive models in a professional setting
- Familiar with training inference and infra pipelines that go from camera input to trajectory output for self-driving or robotics
- Experience with RL (reinforcement learning)
- Strong understanding of modern ML architectures and training techniques
- Experience with model debugging, optimization, and performance tuning
- Background in implementing ML research papers and adapting academic work.
Benefits
- Employee Stock Options
- Paid time off
- Medical/dental/vision insurance
- Life insurance
- Disability insurance
- 401(k)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningmodel evaluationperformance optimizationtransfer learningfine-tuningreinforcement learningdata strategiesmodel debuggingmodel architectureslarge-scale ML models
Soft Skills
leadershipcollaborationcommunicationrapid experimentationprototyping