Senior ML Systems Engineer

Job Description Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA you are expected to report to that location three times a week. Help teach our self‑driving vehicles how to see and understand the world! The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling tools and pipelines that power autonomous vehicle machine learning models within General Motors' AV organization. We operate in the intersection of software engineering, data engineering, and AI/ML, defining the strategies, tooling, and quality controls that create reliable training data at scale. Our tools and platform are used by thousands of users and consumers. We own a modern full‑stack architecture including TypeScript/React, Python, GraphQL, Golang, and ML model services, which powers data‑annotation pipelines and machine‑led training data solutions at foundation‑model scale. We partner closely across AI/ML engineers, Product Operations, Product Management, Data Science, and other ML Platform groups. This role is ideal for an engineer who wants end-to-end ownership of meaningful pieces of the platform, growth toward technical leadership, and direct impact on systems that unblock the next generation of AV capabilities. What You’ll Do Build high‑impact labeling experiences Design, implement, and test scalable, high‑p [... source excerpt omitted ...] design discussions, and technical decisions. Collaborate across the AV stack Work with partner teams (ML, Ops, Product, Data Science, other platform teams) to translate abstract requirements into concrete workflows, APIs, and UIs that hit quality, cost, and latency goals. Your Skills & Abilities Passionate about self‑driving technology and its potential to transform safety, mobility, and the driving experience. Driven to learn new technologies and deepen your expertise across frontend, backend, and data/ML‑adjacent systems. Proven experience shipping and operating end‑to‑end products or features in production. Strong communication and collaboration skills; you can explain trad [... source excerpt omitted ...] ambiguity with cross‑functional partners. Empathetic to user challenges (from labelers to ML engineers to Ops) and excited to turn messy workflows into simple, intuitive tools. Requirements 6+ years of experience building robust distributed platforms and applications. Hands-on experience leveraging AI tools (agentic coding, search, documentation generators, etc) 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 databas