Sr. Machine Learning Engineer; Perception and Tracking

At Ouster, we build sensors and tools for engineers, roboticists, and researchers, enabling safer and more efficient systems. We have transformed LIDAR into a compact, high-performance digital device and offer a full range of high-resolution sensors for autonomous cars, robotics, industrial, and smart infrastructure applications. If you’re motivated by solving big problems, we’re hiring key roles across the company and need your help!

• Architect Unified Models:
  Design and train DNN models that perform Object Detection and Tracking simultaneously, leveraging temporal information to improve consistency.
• Research to Production:
  Evaluate state-of-the-art research papers, prototype concepts, and adapt them into robust, production-grade solutions.
• Deep Model Customization:
  Implement custom loss functions, modify internal model architectures, and design data augmentation strategies to maximize performance.
• Edge Optimization:
  Ensure high accuracy is matched by high efficiency; optimize models for real-time inference and on-device deployment.
• Data Strategy:
  Develop training recipes for data-constrained environments and effective post-training strategies.

• Core Stack:
  • 5+ years proficiency in Python and PyTorch.
  • 3+ years proficiency in C++ for production deployment and optimization.
• Detection & Tracking:
  Deep theoretical and practical understanding of modern object detectors (e.g., Transformers, YOLO variants, R-CNNs) and tracking algorithms (e.g., DeepSORT, Kalman Filters, Optical Flow).
• Architecture Internals:
  Proven experience modifying model architectures via extensive experimentation to meet specific requirements, not solely relying on out-of-the-box APIs.
• Low-Data Regimes:
  Experience improving model generalization with limited data using Transfer Learning, Domain Adaptation, or Few-Shot Learning.
• Mathematical Foundation:
  Strong grasp of linear algebra and probability as it applies to custom loss function design and geometric 3D vision.

• 3D / LiDAR
  
  Experience:
  
  Hands-on experience with 3D Point Cloud data (LiDAR).
• Deployment Tools:
  
  Experience with Tensor
  
  RT, ONNX Runtime, or edge-specific hardware (NVIDIA Jetson, etc.).

The base pay will be dependent on your skills, work experience, location, and qualifications. This role may also be eligible for equity & benefits. ($162,000 - $180,000)

We acknowledge the confidence gap  do not need to meet all of these requirements to be the ideal candidate for this role.

Ouster is an Equal Employment Opportunity employer that pursues and hires a diverse workforce. Ouster does not make employment decisions on the basis of race, color, religion, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military status, or any other basis protected by local, state, or federal laws. Ouster also strives for a healthy and safe workplace, and prohibits harassment of any kind.

Pursuant to the San Francisco Fair Chance Ordinance, Ouster considers qualified applicants with arrest and conviction records for employment. If you have a disability or special need that requires accommodation, please let us know.