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Staff Full Stack Software Engineer - ML Ops Tooling Platform
Staff Full Stack Software Engineer - ML Ops Tooling PlatformZoox • Foster City, CA, United States
Staff Full Stack Software Engineer - ML Ops Tooling Platform

Staff Full Stack Software Engineer - ML Ops Tooling Platform

Zoox • Foster City, CA, United States
18 hours ago
Job type
  • Full-time
Job description

This team owns the data and data platform to support all Perception model training and validation, as well as system validation beyond Perception. The platform supports sample curation, data mining, data labeling, and ML dataset management. High quality data and efficient data flywheel are central to ML model development, enabling teams to efficiently iterate and improve model performance at scale while Zoox expands its business domain.

In this role, you will improve and scale the platform, while also building new features and expanding cross-pillar adoption through Python / C++ tooling, APIs, and data engineering. Your work spans backend API development, data pipelines, and integration with model training and testing workflows, ultimately providing the infrastructure that powers data flywheel at scale.

In this role, you will :

  • Work on the Data Flywheel that supports multiple Perception ML teams with data mining, labeling, and curation, to help ML teams improve model performance via better data.
  • Quickly ramp up on our team's current stack and systems, deliver solutions, and improve solutions based on other teams' feedback
  • Innovate solutions that leverage AI to drive process automation and efficiency
  • Help coach more junior engineers by reviewing their design and implementation

Qualifications

  • 10 YOE+
  • Expert-level proficiency in Python; experienced with or feeling comfortable ramping up C++
  • Strong background in high-performance computing, data processing, and software architecture design and implementation
  • Experience with data query and analysis on a large data warehouse, such as Databricks
  • Experience in working with AND supporting multiple teams (supporting ML teams is preferred), leading other team members
  • Bonus Qualifications

  • Experience in ML and data-driven mode development
  • Knowledge of frontend stack (JavaScript, Vue, or React.js)
  • Experience in tooling / infra that supports multiple teams
  • $250,000 - $300,000 a year

    Compensation and Benefits

    There are three major components to compensation for this position : salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $179,000-$294,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.

    Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

    About Zoox

    Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

    Follow us on LinkedIn

    Accommodations

    If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.

    A Final Note :

    You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

    We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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    Ml Ops Engineer • Foster City, CA, United States

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