Senior ML Validation Engineer
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Job Location:
Sunnyvale, CA - USA
Monthly Salary:
Not Disclosed
Posted on:
3 days ago
Vacancies:
1 Vacancy
Job Summary
Job Description
The Senior ML Validation Research Engineer will lead applied machine learning research focused on improving verification and validation of ML components used in robotics and autonomous driving systems. This role centers on simulation-based evaluation uncertainty modeling scenario coverage automation and transforming advanced ML research into working prototypes that enhance the efficiency accuracy and coverage of ML system validation.
Key Responsibilities
Prototype research concepts into performant tools integrated into CI/CD and large-scale validation pipelines.
Advance ML research for open and and closed loop simulation validation.
Develop scenario generation coverage-guided testing and rare-event discovery tooling.
Create robust metrics predictors uncertainty and Out-of-Distribution detection methods for autonomy ML systems.
Evaluate deep learning modules across perception prediction and planning in realistic sensor and traffic simulation.
Improve behavioral coverage and hazard-aligned metrics used in release readiness decision making.
Collaborate with Simulation Safety Systems Engineering and cross-functional partners.
Author technical documentation white papers and contribute to validation methodology standards.
Research Focus Areas
Scenario synthesis (diffusion models generative models counterfactuals)
Coverage-based and fuzzing-based evaluation for autonomy behavior
Uncertainty estimation calibration conformal prediction OOD detection
Robustness testing and perturbation frameworks
Test suite prioritization failure mining and regression analysis
Required Qualifications
MS 5 years or PhD 3 years in ML Robotics Computer Science or work related experience
Experience with simulation-driven ML evaluation for robotics/autonomy
Strong proficiency in Python PyTorch/JAX/TensorFlow
Demonstrated ability to translate complex ML research ideas into functional prototypes
Experience integrating ML evaluation into CI/CD pipelines
Proven research impact through published work internal tools or patents
Strong communication skills and ability to collaborate cross-functionally
Preferred Qualifications
Experience with autonomy stacks (perception/prediction/planning).
Familiarity with CARLA SVL DriveSim Applied Intuition or equivalent simulation platforms.
Knowledge of Bayesian ML causal inference and sequential testing.
Experience with digital twin systems and sensor simulation.
Understanding of automotive safety standards (ISO 26262 UL 4600 SOTIF).
Experience building validation dashboards and scorecards connected to release criteria.
Success Criteria
Faster detection of ML regressions with improved test efficiency
Improved uncertainty and robustness metrics that support release decisions
Prototype tools integrated into production validation workflows
Tangible contributions to simulation strategy hazard coverage and ML confidence scoring
Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paidin accordance withapplicable state laws. The compensation may not be representative for positionslocatedoutside of New York Colorado California or Washington.
The salary range for this roleis$144700- $261300.The actual basesalarya successful candidate will be offered within this range will vary based on factors relevant to the position.
Bonus Potential: An incentivepayprogram offers payouts based on company performance job level and individual performance.
Benefits:
Benefits: GM offers a variety of health and wellbeing benefit programs.Benefit options include medical dental vision Health Savings Account Flexible Spending Accounts retirement savings plan sickness and accident benefits life insurance paid vacation & holidays tuitionassistanceprograms employeeassistanceprogram GM vehicle discounts and more.
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Required Experience:
Senior IC
Key Skills
- Python
- SOC
- Debugging
- C/C++
- FDA Regulations
- Minitab
- Technical Writing
- GAMP
- OS Kernels
- Perl
- cGMP
- Manufacturing
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