ML Systems Engineer, Data Labeling Engineering – Early Career

• Develop automation and tooling for labeling workflows and data quality, including efficiency dashboards, automated quality assurance, and autolabel review tools
• Collaborate with ML engineers to design and integrate ML-driven data annotation, including pre-labeling, autolabeling, and active learning loops
• Help evolve labeling workflows from human-only processes toward machine-led labeling at scale
• Design, implement, and test scalable, high-performance user experiences and services using modern full-stack and/or frontend technologies
• Ship features across multiple product surfaces to improve the speed and accuracy of data labeling for new models and cities
• Apply production engineering practices including code review, automated testing, observability, CI/CD, and incremental delivery
• Use AI-assisted development workflows such as code assistants, automated documentation, test generation, and operational triage while maintaining code and product quality
• Partner with labelers, ML engineers, Product Operations, Product Management, Data Science, and other cross-functional teams to improve the platform

• Recently completed a bachelor’s, master’s, or PhD degree in Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Machine Learning, or a related STEM field; completed degree must have been awarded within the past 9 months
• Experience building software through coursework, internships, research, personal projects, or prior professional experience
• Programming experience in one or more of Python, Type Script, JavaScript, Go, Java, or C++
• Familiarity with object-oriented design, design patterns, data structures, algorithms, API/interface design, and engineering best practices
• Exposure to building applications, services, data pipelines, or user-facing tools in a collaborative environment
• Ability to learn new technologies, reason about technical tradeoffs, and communicate clearly with engineering and cross-functional partners
• Interest in autonomous vehicles, robotics, machine learning, data-centric AI, or developer and ML platform technologies
• Preferred: graduation between December 2025 and August 2026, with availability to begin employment in 2026
• Preferred experience with Python, Type Script, Go, React, SQL, Redux, gRPC, GraphQL, WebGL, or similar tools
• Preferred familiarity with scalable software system design, data modeling, API/interface design, observability, CI/CD, or test-driven development
• Preferred experience with computer vision, machine learning, data-centric AI, data annotation, data quality, or autolabeling workflows
• Preferred familiarity with data labeling or annotation platforms, annotation user interfaces, workflow engines, or quality systems
• Preferred experience with A/B testing, telemetry, observability systems, data-intensive applications, visualization-heavy applications, AI-assisted engineering workflows, and cross-functional collaboration

Demonstrates expertise in developing automation and tooling for data labeling workflows, with strong programming skills in Python, Type Script, and JavaScript. Proficient in applying production engineering practices and collaborating with cross-functional teams to enhance data quality and user experiences.

• Python Programming
• Type Script Programming
• Data Annotation Workflows
• CI/CD Practices
• Machine Learning Integration

• JavaScript Programming
• Go Programming
• Java Programming
• C++ Programming
• Object-Oriented Design
• Data Structures
• Algorithms
• API Design
• Test-Driven Development
• Data Modeling

• Clear Communication
• Collaborative Problem Solving
• Technical Tradeoff Reasoning
• Adaptability to New Technologies

• Data-Centric AI
• Autonomous Vehicles
• Robotics
• Data Quality
• Machine Learning
• Data Annotation
• Quality Systems
• Workflow Engines
• Cross-Functional Collaboration
• AI-Assisted Engineering

• React
• SQL
• Redux
• GRPC
• GraphQL
• WebGL
• Observability Systems
• Telemetry
• A/B Testing
• Visualization Tools