Senior ML Systems Engineer
WFA Digital Insight
As demand for autonomous vehicle technology grows, so does the need for skilled ML Systems Engineers. With a 25% increase in funding for self-driving car projects in 2025, professionals with expertise in AI, machine learning, and data engineering are in high demand. General Motors stands out as a pioneer in this field, and this role offers a unique chance to work on cutting-edge technology. Before applying, candidates should be aware that a strong background in software engineering, data engineering, and AI/ML is essential, as well as excellent communication and collaboration skills.
Job Description
About the Role
The Senior ML Systems Engineer will play a crucial role in developing and implementing AI-powered labeling tools and machine learning models for General Motors' autonomous vehicle division. This role entails designing, building, and operating hybrid human/machine data labeling tools and pipelines that power autonomous vehicle machine learning models. The successful candidate will work closely with cross-functional teams, including AI/ML engineers, Product Operations, Product Management, and Data Science.As a key member of the Data Labeling Engineering team, you will be responsible for developing high-impact labeling experiences, designing and implementing scalable and high-performance user experiences and services using modern full-stack and frontend technologies. You will also collaborate with ML engineers to design and integrate ML-driven data annotation, helping to move from human-only to machine-led labeling at scale.
What You Will Do
- Design, implement, and test scalable, high-performance user experiences and services using modern full-stack and frontend technologies
- Develop automation and tooling that give ML engineers deep insight into labeling workflows and data quality
- Apply ML to labeling itself, collaborating with ML engineers to design and integrate ML-driven data annotation
- Champion AI-assisted engineering, using and advocating for modern AI-powered development workflows
- Own projects end-to-end, taking ownership of technical projects from problem framing through design, implementation, and rollout
- Drive code reviews, design discussions, and technical decisions
- Collaborate across the AV stack, working with partner teams to translate abstract requirements into concrete workflows, APIs, and UIs
- Level up how ML teams work with data, developing tooling that reduces iteration time from idea to trained model
- Build high-impact labeling experiences, designing and implementing services that directly affect how quickly and accurately data can be labeled for new models and cities
What We Are Looking For
- 6+ years of experience building robust distributed platforms and applications
- Hands-on experience leveraging AI tools to accelerate understanding, implementation, debugging, and delivery of new capabilities
- Proficiency in writing and reviewing high-quality, scalable, and performant full-stack code using technologies and languages like Python, TypeScript, Go, React, SQL, Redux, GraphQL, WebGL
- Solid understanding of relational databases, data modeling, and API design
- Strong fundamentals in object-oriented design and design patterns, data
- Passionate about self-driving technology and its potential to transform safety, mobility, and the driving experience
- Driven to learn new technologies and deepen expertise across frontend, backend, and data/ML-adjacent systems
Nice to Have
- Experience with automated testing and continuous integration/continuous deployment
- Knowledge of cloud-based technologies, such as AWS or Azure
- Familiarity with agile development methodologies
Benefits and Perks
- Flexible and remote work arrangements
- Competitive salary and benefits package
- Opportunities for professional growth and development
- Collaborative and dynamic work environment
- Access to cutting-edge technology and tools
- Recognition and reward for outstanding performance
How to Stand Out
- To stand out as a candidate, be prepared to provide specific examples of your experience with AI-powered development workflows and machine learning model development.
- Make sure your portfolio includes examples of your work with full-stack code, including Python, TypeScript, and React.
- Be prepared to discuss your experience with data engineering and data modeling, as well as your understanding of relational databases and API design.
- When negotiating salary, be aware of the current market rate for ML Systems Engineers and be prepared to discuss your expectations.
- Be cautious of companies that do not provide clear information about their technology stack or development workflows, as this can indicate a lack of transparency or investment in employee growth.
- Consider reaching out to current or former employees to gain insight into the company culture and work environment.
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