Serve Robotics is at the forefront of revolutionizing urban delivery systems through their innovative sidewalk robot technology. As a Senior Data Scientist in Machine Learning, you'll be joining a team of tech industry veterans who are passionate about creating the future of autonomous delivery systems.
The role combines advanced machine learning expertise with practical data engineering skills to develop dependable sidewalk autonomy software. You'll be working on cutting-edge problems involving robotics, machine learning, and computer vision, while focusing on creating scalable solutions that can handle petabytes of multi-modal data.
The position offers an exciting opportunity to work with a diverse, agile team that values collaborative problem-solving and respectful communication. You'll be instrumental in developing and implementing data-centric approaches to machine learning, from automated feature engineering to active learning and fine-tuning models on curated datasets.
Key technical aspects include working with various ML frameworks, cloud platforms, and modern MLOps tools. The role requires expertise in Python, SQL, and data pipeline development, along with a strong foundation in machine learning fundamentals. You'll be involved in designing auto-labeling systems, optimizing ETL processes, and ensuring seamless integration of data and machine learning workflows.
The company offers competitive compensation ($160K-$200K) with equity, and the position is remote-friendly while maintaining a presence in Los Angeles. This is an excellent opportunity for someone who wants to make a significant impact in the autonomous delivery space while working with a team that's focused on building practical, user-friendly solutions for real-world problems.
The ideal candidate will bring not just technical expertise but also strong communication skills and the ability to work effectively with cross-functional teams. The role offers growth potential as the company expands its robotic delivery services from current operations in Los Angeles to broader deployment.