- Company Name
- Waymo
- Job Title
- Senior Machine Learning Engineer, Perception, Semantics
- Job Description
-
**Job Title**
Senior Machine Learning Engineer, Perception, Semantics
**Role Summary**
Lead the design, training, evaluation, and deployment of end‑to‑end machine learning models that enable autonomous vehicles to perceive complex scenes—including vulnerable road users, traffic controls, and unstructured environments—while optimizing for real‑time, on‑device performance.
**Expactations**
- Deliver production‑grade perception models that meet safety and performance targets.
- Own the full ML lifecycle from data acquisition to model deployment.
- Publish research in top ML/CV conferences and advance the state‑of‑the‑art.
- Drive cross‑domain collaboration with hardware, software, and safety teams.
**Key Responsibilities**
- Design and train deep neural networks for object classification, detection, tracking, pose estimation, and action recognition.
- Build and maintain data pipelines: mining, labeling, augmentation, and dataset versioning.
- Optimize models for low‑latency, edge‑inference with quantization, pruning, and other techniques.
- Integrate multi‑modal sensor data (camera, LiDAR, radar) into perception pipelines.
- Conduct rigorous model evaluation, ablation studies, and performance benchmarking.
- Deploy models to production, monitor real‑world behavior, and perform post‑deployment tuning.
- Mentor junior engineers, review code, and contribute to technical strategy and roadmap.
**Required Skills**
- 4+ years of ML engineering focused on computer vision and deep learning for perception tasks.
- Deep expertise in object detection, tracking, pose estimation, and action recognition.
- Proficiency with TensorFlow, PyTorch, or JAX and experience writing production‑grade code in Python (and CUDA if applicable).
- Experience building multi‑modal perception systems (camera + LiDAR + radar).
- Knowledge of foundation models, transfer learning, domain adaptation, and few‑shot learning techniques.
- Strong background in model optimization for on‑device deployment (quantization, pruning, latency analysis).
- Demonstrated ability to evaluate models, run experiments, and communicate findings to both technical and non‑technical stakeholders.
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or a closely related field (PhD preferred or equivalent experience).
- Preferred: Publications in leading ML/CV conferences (NeurIPS, ICML, CVPR, ICCV, ECCV).