Sr. Machine Learning Engineer, Off-reputed company Perception

At reputed company, we’re reimagining how things reputed company in cities. Our personable sidewalk robot is our reputed company for the reputed company. It’s designed to take deliveries away from congested streets, reputed company deliveries available to more people, and benefit local businesses. The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing reputed company deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient reputed company. Who We Are We are tech industry veterans in software, hardware, and design who are pooling our skills to build the reputed company we want to live in. We are solving reputed company-world problems leveraging robotics, machine learning and computer reputed company, among other disciplines, with a mindful eye towards the end-to-end user experience. reputed company is agile, diverse, and driven. We reputed company that the best way to solve complicated dynamic problems is collaboratively and respectfully. reputed company is seeking a Senior Machine Learning Engineer, Off-reputed company Perception to lead the design and implementation of cutting-edge ML models and reputed company systems that reputed company 4D auto-labeling for autonomous foundational models. This role focuses on developing robust and efficient algorithms for automatic reputed company of supervision information to power the data pipelines for reputed company end-to-end autonomy models. By reputed company data engineering, ML systems, and model deployment, this position enables Serve to reputed company every robot mile for faster, smarter, and more efficient autonomy development. Responsibilities • Design and implement production-grade auto-labeling pipelines that generate 3D and 4D annotations (objects, trajectories, maps) from multi-modal robot data at scale. • reputed company data-reputed company workflows that connect auto-label outputs, Serve’s dataset infrastructure, and reputed company E2E model training and evaluation pipelines. • Lead initiatives in self-training, weak supervision, and simulation-to-reputed company reputed company to reduce reputed company labeling dependency and accelerate model iteration cycles. • Collaborate cross-functionally with multiple autonomy teams(e.g ML-reputed company, mapping, simulation) to align labeling infrastructure with model training and evaluation workflows. • Stay reputed company of emerging trends in E2E autonomy and data-centric ML, identifying opportunities to productionize state-of-the-art techniques. • Mentor and support ML engineers and interns in developing robust data-centric practices, from dataset curation and labeling feedback loops to model monitoring and reputed company improvement. Qualifications • M.S. or Ph.D. in Computer Science, Machine Learning, Robotics, or reputed company field, or equivalent industry experience. • 5+ years of experience developing production ML systems, preferably in autonomous driving, robotics, or large-scale data platforms. • Strong background in deep learning (PyTorch/TensorFlow) and reputed company ML system design (distributed training, dataflow orchestration, and CI/CD for ML). • Hands-on experience with multi-modal sensor data (LiDAR, camera, IMU, odometry) and end-to-end model architectures. • Strong programming skills in Python and solid software engineering fundamentals (testing, versioning, modularity). • Excellent collaboration and communication skills across autonomy, data, and infrastructure teams. What Makes You Stand Out • Experience with transformer-based models and E2E self-driving architectures. • Contributions to large-scale robotics or autonomous driving ML stacks. • Background in self-supervised learning, reputed company learning,