Software Engineer, ML Infrastructure
Description For Software Engineer, ML Infrastructure
Serve Robotics is revolutionizing urban delivery with their innovative sidewalk robots, creating a more efficient and sustainable future for local deliveries. As an ML Infrastructure Engineer, you'll be at the heart of developing and maintaining the crucial machine learning platform that powers their autonomous delivery system.
The role involves working with cutting-edge technologies and large-scale data processing systems, including Apache Beam, Kubernetes, and various cloud services. You'll be responsible for building and improving ML pipelines, managing data processing workflows, and ensuring the efficient operation of the ML infrastructure that supports the company's autonomous delivery robots.
The ideal candidate will bring a strong background in computer science, with specific expertise in data engineering and machine learning systems. You'll need at least 2 years of experience working with ML training pipelines and cloud applications, along with proficiency in languages like Python, C++, or Go. Your experience with computer vision and deep learning will be essential in understanding and supporting the ML models that power the robots.
This is an exciting opportunity to join a team of industry veterans who are combining robotics, machine learning, and thoughtful design to solve real-world problems. The company culture emphasizes collaborative problem-solving and respect, making it an ideal environment for those who want to contribute to the future of autonomous delivery while working with a diverse and driven team.
Working at Serve Robotics means being part of a mission to transform how things move in cities, with their robots already making successful deliveries in Los Angeles. The company offers competitive compensation including equity, ensuring you'll share in the success you help create. If you're passionate about building scalable ML infrastructure and want to be part of shaping the future of autonomous delivery, this role offers the perfect blend of technical challenge and meaningful impact.
Responsibilities For Software Engineer, ML Infrastructure
- Develop and maintain ML infrastructure, including sensor data ETL pipelines, hard example data mining, and continuous training pipelines
- Develop MLOps system for managing lifecycle of ML cloud training and inference as a service pipelines
- Work with ML engineers to design metrics for ML tasks to mine sensor data
- Design and implement algorithms for ranking/scoring annotation candidates
- Work with annotation provider on setting up the annotation process
- Make sensor data and derivatives accessible for Robotics Engineers
Requirements For Software Engineer, ML Infrastructure
- BS or MS in computer science with focus in data engineering and ML systems
- 2+ years of industry experience building ML training and validation pipelines
- Experience with building native cloud applications
- Experience with large scale data processing pipelines in production
- Proficient in C++, Python, or Go
- Hands-on experience and knowledge of Computer Vision and Deep Learning
- Strong tendency to automate workflows
Benefits For Software Engineer, ML Infrastructure
- Equity compensation
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