AI/ML Engineer for AV Platform Development
Budget: $15 – $25 USD
AI/ML Engineer
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‑performance user experiences and services using modern full‑stack and/or frontend technologies. You’ll ship features spanning multiple surface-areas that directly affect how quickly and accurately we can label data for new models and cities.
Level up how ML teams work with data
Develop automation and tooling that give ML engineers deep insight into labeling workflows and data quality (e.g., efficiency dashboards, auto‑QA, autolabel review tools), reducing iteration time from idea to trained model.
Apply ML to labeling itself
Collaborate with ML engineers to design and integrate ML‑driven data annotation (pre‑labeling, autolabeling, active learning loops), helping us move from human‑only to machine‑led labeling at scale.
Champion AI‑assisted engineering
Use and advocate for modern AI‑powered development workflows (code assistants, automated documentation, test generation, etc.) to increase velocity while maintaining quality.
Own projects end‑to‑end
Take ownership of technical projects from problem framing through design, implementation, and rollout. Drive code reviews, design discussions, and technical decisions.
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 databases, data modeling, and API design .
Strong fundamentals in object‑oriented design and design patterns , data structures , algorithms , and engineering best practices (TDD, code quality, observability, CI/CD).
Experience developing and operating cloud‑based applications .
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‑performance user experiences and services using modern full‑stack and/or frontend technologies. You’ll ship features spanning multiple surface-areas that directly affect how quickly and accurately we can label data for new models and cities.
Level up how ML teams work with data
Develop automation and tooling that give ML engineers deep insight into labeling workflows and data quality (e.g., efficiency dashboards, auto‑QA, autolabel review tools), reducing iteration time from idea to trained model.
Apply ML to labeling itself
Collaborate with ML engineers to design and integrate ML‑driven data annotation (pre‑labeling, autolabeling, active learning loops), helping us move from human‑only to machine‑led labeling at scale.
Champion AI‑assisted engineering
Use and advocate for modern AI‑powered development workflows (code assistants, automated documentation, test generation, etc.) to increase velocity while maintaining quality.
Own projects end‑to‑end
Take ownership of technical projects from problem framing through design, implementation, and rollout. Drive code reviews, design discussions, and technical decisions.
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 databases, data modeling, and API design .
Strong fundamentals in object‑oriented design and design patterns , data structures , algorithms , and engineering best practices (TDD, code quality, observability, CI/CD).
Experience developing and operating cloud‑based applications .
Related categories:
Python
SQL
Cloud Computing
API
Full Stack Development
GraphQL
Data Modeling
Software Engineering
CI/CD
AI Development