Lead Machine Learning Engineer

The role

This role develops and scales large-scale machine learning training systems for multimodal robotics data. You will optimize distributed training pipelines, neural network architectures, and data processing workflows to improve training efficiency and maximize GPU utilization.

What you will do

• Design and maintain training systems for petabyte-scale multimodal datasets.
• Identify and resolve bottlenecks in the training pipeline to maximize GPU utilization.
• Develop and refine neural network architectures for autonomy tasks.
• Create and adjust loss functions and training strategies.
• Configure, monitor, and maintain large-scale distributed training jobs.
• Implement scalable systems to preprocess, transform, and augment large robotics datasets.
• Integrate new models, experiments, and training approaches into the production training pipeline.
• Analyze training metrics, model outputs, and experiment logs.
• Develop tools and workflows for running experiments and tracking results.

Required qualifications

• Master’s or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline.
• Minimum of 5 years of professional experience developing, training, and deploying machine learning models in production environments.
• Hands-on experience training machine learning models across multiple GPUs or compute nodes.
• Familiarity with distributed training frameworks and large dataset handling.
• Strong programming skills in Python for implementing machine learning models, data pipelines, and training workflows.
• Solid knowledge of core concepts such as neural networks, optimization algorithms, loss functions, model evaluation, and training methodologies.

Nice to have

• Experience identifying and resolving training bottlenecks related to compute utilization, memory usage, and data throughput in machine learning systems.
• Experience training machine learning models on robotics or autonomous driving datasets involving multimodal sensor inputs such as camera video, LiDAR point clouds, radar, or telemetry data.
• Experience developing models that combine multiple data modalities into a unified learning system.
• Peer-reviewed publications or significant research contributions in machine learning, robotics, or related areas.

About the company

Serve Robotics is building sidewalk robots for commercial deliveries. The team consists of tech industry veterans in software, hardware, and design.