Software Engineer, ML Infrastructure
Description For Software Engineer, ML Infrastructure
Serve Robotics is revolutionizing urban delivery with their innovative sidewalk robots, currently operating successfully in Los Angeles. They're seeking a Software Engineer specialized in ML Infrastructure to join their diverse and agile team of tech industry veterans. This role is crucial for scaling their ML capabilities as they expand their robot fleet across cities.
The position focuses on building and maintaining the ML infrastructure that powers their autonomy systems. You'll be working with terabytes of sensor data, developing scalable processing pipelines, and implementing sophisticated ML training and inference systems. The role combines elements of data engineering, ML operations, and infrastructure development, making it perfect for someone who enjoys working at the intersection of big data and machine learning.
As part of the ML Infrastructure team, you'll be responsible for creating robust data processing pipelines, improving active learning systems, and ensuring the scalability of training jobs and inference endpoints. You'll work closely with autonomy engineers and ML teams to enhance developer productivity and platform reliability.
The ideal candidate should have strong Python skills, experience with cloud platforms, and a solid understanding of distributed computing. Experience with tools like Airflow, various databases (including vector search), and IaC/CI/CD would be particularly valuable. The role offers competitive compensation ($119K-$160K) plus equity, and the opportunity to work remotely while contributing to the future of urban delivery technology.
This is an excellent opportunity for a mid-level engineer who wants to make a significant impact in the robotics and AI space while working with cutting-edge technology and solving real-world problems. The collaborative and respectful team culture, combined with the technical challenges of scaling ML infrastructure, makes this an exciting role for someone passionate about both technology and innovation.
Responsibilities For Software Engineer, ML Infrastructure
- Develop and maintain highly scalable data processing pipelines for data curation, annotation, search and ml feature extraction
- Build and improve active learning pipelines
- Ensure scalability of training jobs and inference endpoints
- Develop and maintain orchestration and scheduling systems
- Collaborate with autonomy engineers to build new features for autonomy data platform
- Build integrations with annotation providers
- Develop infrastructure components using IaC and implement CI/CD processes
- Develop monitoring and alerting frameworks
- Collaborate with ML Engineers in accelerating ml development velocity
- Work with the data team to ensure SLAs around data quality and availability
Requirements For Software Engineer, ML Infrastructure
- BS or MS in computer science (or equivalent work experience) with focus in data engineering and machine learning
- 2+ years of industry experience developing big data processing and/or machine learning pipelines
- 1+ years of hands on experience with cloud platforms (AWS/GCP/Azure)
- Proficient in Python
- Solid understanding of system design fundamentals and distributed computing concepts
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