Perception Machine Learning Engineer - Continuous Learning

Job description

Job responsibilities

• Architect Infrastructure: Design and scale the data pipelines needed to mine, ingest, and manage massive volumes of sensor data from our fleet.
• Drive Model Improvement: Deploy active learning algorithms to continuously identify and select the most impactful data for training, ensuring our large models continuously adapt to new environments with incremental…
• Ensure Model Quality: Develop methods and recipes for evaluating real-world performance of our models, and detecting regressions in model updates. Develop and maintain ground-truth free performance metrics.
• Optimize Data Efficiency: Conduct large-scale experiments focused on data balancing, subset selection, and label quality optimization.
• Solve Long-Tail Challenges: Develop robust mining, training and evaluation pipelines for rare, safety-critical real-world scenarios.
• Innovate with Model Signals: Utilize uncertainty estimation, confidence scores, and embedding space analysis to uncover model blind spots and guide automated data acquisition.
• Collaborate Cross-Functionally: Work closely with researchers and operations teams to iterate on the end-to-end model development lifecycle.

Job requirements

• A bachelor’s degree in Machine Learning, Robotics, or Computer Science. 3+ years of professional experience in Machine Learning and/or Computer Vision.
• Proven, hands-on experience applying active learning in production environments.
• Strong expertise in building large-scale ML data pipelines (mining, extraction, auto-labeling, ingestion).
• Deep understanding of data curation—balancing, core set selection, and sampling—to optimize model performance.
• Proficiency in Python and deep learning frameworks (PyTorch or JAX).
• Strong software engineering skills for writing robust, production-ready code.