Senior Software Engineer, Machine Learning Infrastructure
Kodiak - Mountain View, CA
posted 3 days ago
About the position
Kodiak Robotics, Inc. was founded in 2018 and has become the trusted world leader in autonomous ground transportation committed to a safer and more efficient future for all. The company is developing an industry-leading artificial intelligence (AI) powered technology stack purpose-built for driverless military and long-haul trucking applications. Kodiak's unique modular hardware approach integrates sensors into a streamlined sensor-pod structure that optimizes for perception, scalability, and maintainability. The company autonomously delivers freight daily for its commercial customers across the Sun Belt states and for Atlas Energy in the Permian Basin. Kodiak also leverages its commercial self-driving software to develop, test and deploy autonomous capabilities for the U.S. Department of Defense. We are looking for a highly skilled Infrastructure Engineer to join the Perception team and build world-class deep learning training, evaluation, and deployment infrastructure for the development of the perception and prediction modules of our self-driving semi trucks.
Responsibilities
- Design and implement Kodiak's infrastructure for training, evaluating, and deploying deep learning models in efficient Python and C++ code
- Develop and optimize push-button training pipelines in distributed environments
- Develop metrics to measure model, perception system, and overall self-driving performance
- Build systems to track metrics over time and enable comparison of experiments
- Develop systems for finding failure cases, visualizing predictions, and pinpointing areas for improvement
- Create systems to track, segment, and select data to be used in training or reinforcement, including synthetic and machine-generated labels
- Measure and optimize deep learning network and detection runtime performance using state of the art techniques
- Enable continuous integration and deployment of model improvements
- Collaborate closely with other experts in sensors, perception, prediction, planning, and systems engineering teams
Requirements
- Strong technical background. BS, MS or PhD with academic or industry experience in designing and implementing deep learning, ML, or data analytics infrastructure.
- Skilled in Python/C++ and strong problem-solving skills.
- Very strong software engineering skills and experience building high-reliability applications used by other engineers.
- Solid understanding of metrics, data analysis, and scientific evaluation.
- Ability to build and iterate quickly.
- Hands on experience working with production machine learning pipelines, from dataset collection and labeling to training and validation.
- Great communicator with experience writing clear, concise, and detailed documentation.
Nice-to-haves
- Strong knowledge of data processing pipelines for training ML models in the cloud.
- Bonus points for understanding the specific subtleties in measuring and evaluating the performance of a robot and its submodules.
- A team player who takes ownership and works with the team to deliver exceptional results.
Benefits
- Competitive compensation package including equity and biannual bonuses
- Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Anthem, and Guardian (including a medical plan with infertility benefits)
- Flexible PTO and generous parental leave policies
- Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
- Long Term Disability, Short Term Disability, Life Insurance
- Wellbeing Benefits - Headspace, One Medical, Gympass, Spring Health
- Fidelity 401(k)
- Commuter, FSA, Dependent Care FSA, HSA
- Various incentive programs (referral bonuses, patent bonuses, etc.)
