Senior/Staff Software Engineer, ML Data Infrastructure

Responsibilities

• Design and develop unified, introspectable, large-scale batch and streaming data pipelines that ingest and process data across a wide range of use cases relevant to evaluation.
• Create and implement a storage system capable of accommodating both the large volume and diverse range of evaluation and performance metrics.
• Construct intuitive dashboards and reports to present evaluation results, facilitating straightforward comparisons that highlight both improvements and regressions of the ML components and the overall system.
• Develop and maintain continuous testing and monitoring systems to guarantee the integrity and resilience of our data and associated data pipelines.
• Develop data mining tools with applied ML techniques to support data discovery needs from Autonomy including Perception, Behavior, and Mapping.
• Develop data annotation tools to support first-party and third-party labeling workforce to provide high fidelity perception, mapping, and driving trajectory labels.
• Scale data annotation labels with applied State-of-the-art ML techniques.

Requirements

• Degree in BS, MS, or Ph.D, plus 4 years of relevant work experience.
• Strong proficiency in Python or similar languages.
• Domain experience: Experience working with large-scale data and building scalable & reliable systems/data pipelines; ability to understand and design complex systems.
• Engineering leadership: Experience setting team or project product and technical vision, timelines, and prioritization; being a Technical Lead, mentoring and support junior engineers.
• Technical excellence: Ability and willingness to deep dive into implementation, driving technical standards and best practices across broader software organization.
• Bachelor's degree in Computer Science, Electrical Engineering, or a closely related field.

Nice-to-Haves

• Strong proficiency in C++ or other high-performance low-level languages.
• Strong knowledge of GCP, GCS, BigQuery, or PostgreSQL.
• Knowledge of data engineering, and its tooling and best practices.
• Knowledge of batch and streaming data processing, warehousing, and analytics solutions.
• Experience working with large-scale distributed data systems.
• Experience with system & framework design.
• Experience with data workflow orchestration platforms.

Compensation

• Base pay range: $193,930 - $352,290 (depending on experience, qualifications, education, location, and skills).
• Eligible for annual performance bonus, equity, and competitive benefits package.