Staff ML Systems Engineer (AI/ML)

Location: Sunnyvale, California, United States; categorized as hybrid, with reporting to the specific location at least 3 times a week. Travel required up to 25%. Relocation benefits are available for qualifying candidates.

Salary: $171,700–$303,900 base salary per year, plus potential incentive pay.

Company

hirify.global is an automotive corporation developing autonomous-vehicle technologies with a vision focused on zero crashes, zero emissions, and zero congestion.

What you will do

• Define the platform vision and incremental roadmap for human/machine data-labeling tools and pipelines.
• Own technical projects end to end, from problem framing and design through implementation, rollout, code reviews, and technical decisions.
• Collaborate with ML Engineering, Operations, Product, Data Science, and platform teams to deliver workflows, APIs, and UIs meeting quality, cost, and latency goals.
• Build automation and tooling such as efficiency dashboards, auto-QA, and autolabel review tools to improve data quality and reduce model iteration time.
• Design and integrate ML-driven annotation, including pre-labeling, autolabeling, and active-learning loops.
• Build scalable, high-performance labeling experiences and services while advocating AI-assisted engineering workflows.

Requirements

• 8+ years of experience building robust distributed platforms and applications.
• Hands-on experience leveraging AI tools for agentic workflows, knowledge acquisition, documentation generation, operational triage, debugging, and delivery.
• Proficiency writing and reviewing scalable, performant full-stack code using technologies such as Python, TypeScript, Go, React, SQL, Redux, gRPC, GraphQL, and WebGL.
• Strong understanding of scalable software system design, including data modeling and API/interface design.
• Strong fundamentals in object-oriented design, design patterns, data structures, algorithms, TDD, code quality, observability, and CI/CD.
• Experience shipping and operating end-to-end products or features in production.
• Strong communication and collaboration skills, including explaining tradeoffs, influencing peers, and working through ambiguity.
• Ability to learn new technologies across frontend, backend, and data/ML-adjacent systems.
• Empathy for labelers, ML engineers, and Operations users, with a focus on creating simple, intuitive tools.

Nice to have

• Close collaboration experience with customers, product managers, designers, and/or user experience researchers.
• Experience with computer vision, machine learning, or data-centric AI projects, especially data annotation, data quality, or autolabeling loops.
• Familiarity with data-labeling and annotation platforms used by large labeling workforces.
• Experience with A/B testing and telemetry/observability systems.
• Experience developing data-intensive or visualization-heavy applications.
• Passion for self-driving or robotics technology.

Culture & Benefits

• Hybrid work arrangement with regular onsite collaboration and travel of less than 25%.
• Medical, dental, vision, Health Savings Account, and Flexible Spending Account options.
• Retirement savings, sickness and accident benefits, life insurance, paid vacation, and paid holidays.
• Tuition assistance, employee assistance programs, and GM vehicle discounts.
• Inclusive workplace focused on belonging, safety, mobility, and meaningful change.

Hiring process

• Role-related assessments and pre-employment screening may be required where applicable.