Sr. Machine Learning Engineer, VLA-Based Planning

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make 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 commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

We’re looking for a motivated ML champion to join our AI team, where you’ll apply advanced machine learning techniques to refine agent prediction and planning models using multi-modality data and support Serve’s robots to navigate through complex sidewalk environments safely and reliably. You will also lead cross-functional collaborations to elevate overall robot behavior and intelligence.

Responsibilities

• Design and develop next-generation learning-based prediction and planning pipelines to support the scalable deployment of a growing robot fleet.

• Research, prototype, and implement state-of-the-art machine learning algorithms—such as imitation learning and reinforcement learning—for the autonomy stack. Stay up to date with the latest advances in prediction and end-to-end modeling.

• Curate and maintain diverse, real-world datasets to train and rigorously evaluate prediction and planning models across a wide range of scenarios.

• Analyze model performance across key metrics and drive optimizations for reliability, computational efficiency, and real-world deployability.

• Collaborate cross-functionally to define robust testing and validation processes for learning-based models, contributing to more intelligent and adaptable robot behaviors.

Qualifications

• Master's degree in Computer Science, Robotics, Electrical Engineering, or a related field with 5+ years of industry experience in building perception and prediction modules for robotics / AV stack.

• Hands-on experience with machine learning frameworks (TensorFlow, PyTorch, etc.).

• Exposure to state-of-the-art research or publications in perception and prediction approaches.

• Strong background in sensor fusion (especially lidar and camera) and modern transformer-based model architecture.

• Proven track record of building ML pipelines and deploying models in production.

• Proficient in Python and C++, Someone who has a high bar to write production quality code.

• Experience with large-scale real-world dataset curation and management.

What makes you standout

• PhD in Computer Science, Robotics, Electrical Engineering, or a related field with 5+ years of industry experience in building perception and prediction modules for robotics / AV stack.

• In-depth knowledge of simulation environments or real-time testing in robotics.

• Experience working with foundational models, including end-to-end architectures, Vision-Language Models (VLM), and Vision-Language-Action (VLA) models.

• Open source project contributor.

• Extensive experience with GCP or AWS, Kubernetes and Docker.