ML Systems Engineer, Data Labeling Engineering – Early Career

Jobtailor; Sunnyvale (CA); On-site; USD 110,000 - 160,000; Full time

Job summary

Jobtailor in Sunnyvale, CA, is seeking a software engineer to develop automation and tooling for labeling workflows and data quality. You will collaborate with ML engineers to design ML-driven data annotation, including pre-labeling and autolabeling, and help scale labeling to support new models and cities.

You will design and test scalable, high-performance user experiences using modern frontend technologies, ship features across product surfaces, and apply production engineering practices such

Qualifications

• Bachelor’s/Master’s/PhD in CS/CE/SE/AI/ML or related STEM field; awarded within the last 9 months.
• Experience building software through coursework, internships, research, personal projects, or prior professional experience.
• Programming experience in Python, TypeScript, JavaScript, Go, Java, or C++.
• Familiarity with OO design, patterns, data structures, algorithms, API/interface design, and engineering best practices.

Responsibilities

• 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.

Skills

Python Programming

TypeScript Programming

JavaScript Programming

Data Annotation Workflows

CI/CD Practices

Machine Learning Integration

Data Quality

AI-Assisted Engineering

React

SQL

Redux

GRPC

GraphQL

WebGL

Observability Systems

Telemetry

A/B Testing

Visualization Tools

Education

Bachelor’s/Master’s/PhD in Computer Science, Computer Engineering, Software Engineering, AI, ML, or related STEM field; awarded within past 9 months

Tools

React

SQL

Redux

GRPC

GraphQL

WebGL

Observability Systems

Telemetry

A/B Testing

Visualization Tools

Job description

• 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

Requirements

• 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, TypeScript, 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, TypeScript, 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

Core Competencies

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

Highest-signal resume keywords

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

Hard Skills

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

Soft Skills

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

Industry Keywords

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

Tools & Technologies

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