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Senior/Staff Machine Learning Engineer

Exclusive opportunity

Onsite

Senior/Staff Machine Learning Engineer

PlusAI

Senior/Staff Machine Learning Engineer

Skills

Deep LearningPythonPyTorchMachine Learning

2 months ago

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Important information


Salary:

$130,000 – $220,000 / year

Location:

San Francisco, CA, USA

Work mode:

Onsite

Published on:

7 September 2026

What they need


Who you are

  • BS, MS, or PhD in Computer Science, Robotics, Machine Learning, or a related field
  • 4+ years of experience developing machine learning systems for robotics, autonomous driving, or other real-time decision-making systems
  • Strong Python programming skills and experience with modern deep learning frameworks such as PyTorch
  • Strong understanding of deep learning, sequence modeling, transformers, diffusion models, or other modern ML architectures
  • Experience designing datasets, experiments, validation methodologies, and metric-driven model evaluation
  • Strong software engineering skills with experience developing and maintaining production-quality software
  • Excellent debugging and analytical problem-solving skills, with the ability to investigate complex issues across datasets, model behavior, and production systems
  • Experience analyzing edge cases, tracing failures to their root cause, and improving model robustness through systematic experimentation
  • Experience designing validation methodologies, automated testing, and monitoring to ensure correctness, safety, and production reliability
  • Strong ownership mindset with the ability to drive problems from investigation through implementation, validation, and deployment
  • Excellent communication skills and experience collaborating across cross-functional engineering teams
  • Experience with planning, prediction, motion forecasting, or trajectory generation
  • Experience deploying machine learning models into production environments
  • Working knowledge of modern C++ and production software development
  • Experience with TensorRT, ONNX Runtime, CUDA, or ML inference optimization
  • Experience with large-scale distributed training or cloud-based ML infrastructure
  • Publications or open-source contributions in machine learning, robotics, or autonomous driving
  • Candidates who stand out typically have one or more of the following:
  • Deep expertise in autonomous vehicle planning or motion prediction
  • Experience developing production ML systems for safety-critical applications
  • Experience leading technical direction for large ML projects
  • Strong intuition for balancing model quality, robustness, latency, and deployment constraints
  • Demonstrated ability to solve ambiguous, cross-functional engineering problems involving machine learning, software systems, and autonomous driving

What the job involves

  • Develop state-of-the-art machine learning models for autonomous vehicle planning using rich map, perception, routing, and contextual sensor data
  • Design and implement model architectures for trajectory generation, behavior planning, and decision making that balance accuracy, robustness, interpretability, and runtime efficiency
  • Own the end-to-end machine learning lifecycle, including data curation, feature engineering, experimentation, training, evaluation, deployment, monitoring, and continuous improvement
  • Design rigorous offline evaluation methodologies, validation pipelines, and metrics to measure planning quality, safety, robustness, and generalization
  • Analyze model behavior, investigate failure cases, and improve performance through systematic error analysis and targeted experimentation
  • Collaborate closely with runtime, perception, prediction, mapping, and systems teams to deploy scalable machine learning solutions into production
  • Design validation strategies and rule-based guardrails to ensure generated trajectories are feasible, safe, and compliant with traffic rules
  • Stay current with advances in machine learning, robotics, and autonomous driving, translating research innovations into production systems
  • Ensure technical work complies with the company's Quality Management System (QMS), customer requirements, regulatory standards, and internal engineering processes

Benefits

  • Unlimited PTO: Unlimited paid time off on top of company holidays to recharge and enjoy as needed
  • Flexible working: Flexibile work arrangements and technology to help manage life's demands at the office and remote
  • Health benefits: Tiered options in medical, dental, and vision insurance to fit your unique needs
  • Future building: Equity, 401k and FSA options for all eligible employees to help build for your future
  • Professional development: Company-sponsored professional development opportunities such as conferences, training, and workshops
  • Catered lunches: Daily catered lunches at both of our Santa Clara and Fremont offices

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