Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
Scoutfield Logo

See all jobs on Scoutfield

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
General Motors

Staff ML Systems Engineer

General Motors

. Define the platform vision and roadmap .

Posted 11/5/2026full-timeUnited StatesLead💰 $171,700 - $303,900 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building robust distributed platforms and applications, with a strong focus on scalable software system design, API/interface design, and leveraging AI tools for automation and efficiency. Proven ability to collaborate across teams and translate stakeholder needs into actionable development roadmaps.

Highest-signal resume keywords
8+ Years Experience In Distributed PlatformsProficiency In Python, TypeScript, Go, ReactExperience With TDD And CI/CDStrong Communication And Collaboration SkillsUnderstanding Of Scalable Software System Design

ATS Keywords

Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Full-Stack Code DevelopmentObject-Oriented DesignData ModelingAlgorithmsEngineering Best PracticesCode QualityObservabilityAPIs And Interface DesignAutomation And Tooling DevelopmentData Annotation Techniques
Soft Skills
Strong CommunicationCollaborationEmpathy For Users
Tools & Technologies
AI ToolsGRPCGraphQLWebGLReduxAutomation ToolsEfficiency DashboardsAuto-QA ToolsData Labeling PlatformsTelemetry Systems
Industry Keywords
Machine LearningData-Centric AIComputer VisionData AnnotationRobotics Technology

Tech Stack

Tools & technologies
GraphQLGRPCPythonReactReduxSQLTypeScriptGo

About the role

Key responsibilities & impact
  • Define the platform vision and roadmap
  • Work with cross-team and cross-functional leads to understand current and future needs
  • Translate stakeholder input into an aligned platform vision and incremental development roadmap
  • Own technical projects end-to-end from problem framing through design, implementation, and rollout
  • Drive code reviews, design discussions, and technical decisions
  • Collaborate with ML Engineering, Operations, Product, Data Science, and other platform teams
  • Translate abstract requirements into workflows, APIs, and UIs meeting quality, cost, and latency goals
  • Develop automation and tooling for ML engineers to understand labeling workflows and data quality
  • Build efficiency dashboards, auto-QA, and autolabel review tools
  • Design and integrate ML-driven data annotation, pre-labeling, autolabeling, and active learning loops
  • Design, implement, and test scalable, high-performance user experiences and services
  • Ship features across multiple platform surface areas affecting data-labeling speed and accuracy
  • Use and advocate for AI-powered development workflows, including code assistants, automated documentation, and test generation

Requirements

What you’ll need
  • 8+ years of experience building robust distributed platforms and applications
  • Hands-on experience leveraging AI tools, including agentic workflows, knowledge acquisition, documentation generation, and operational triage
  • Proficiency writing and reviewing high-quality, scalable, performant full-stack code
  • Experience with Python, TypeScript, Go, React, SQL, Redux, gRPC, GraphQL, WebGL, or similar technologies
  • Understanding of scalable software system design, data modeling, and API/interface design
  • Strong fundamentals in object-oriented design, design patterns, data structures, algorithms, and engineering best practices
  • Experience with TDD, code quality, observability, and CI/CD
  • Proven experience shipping and operating end-to-end products or features in production
  • Strong communication and collaboration skills
  • Ability to learn technologies across frontend, backend, and data/ML-adjacent systems
  • Passion for self-driving and robotics technology
  • Empathy for labelers, ML engineers, and Operations users
  • Bonus: collaboration with customers, product managers, designers, and/or user experience researchers
  • Bonus: experience with computer vision, machine learning, or data-centric AI projects
  • Bonus: familiarity with data labeling/annotation platforms or tools
  • Bonus: experience with A/B testing and telemetry/observability systems
  • Bonus: experience developing data-intensive or visualization-heavy applications

Benefits

Comp & perks
  • Incentive pay program with payouts based on company performance, job level, and individual performance
  • Medical insurance
  • Dental insurance
  • Vision insurance
  • Health Savings Account
  • Flexible Spending Accounts
  • Retirement savings plan
  • Sickness and accident benefits
  • Life insurance
  • Paid vacation and holidays
  • Tuition assistance programs
  • Employee assistance program
  • GM vehicle discounts
  • Hybrid work arrangement
  • Relocation benefits for qualifying candidates