Sr. Software Analyst, Data, Autonomy

Rivian•Palo Alto, CA

About The Position

In this role, you will lead strategic planning and coordination of 3D/2D annotation projects, working closely with both internal and external partners. A key responsibility is rigorous vendor management, ensuring the quality of deliverables, resolving defects, and facilitating feature enhancements. Furthermore, the role encompasses developing policies, setting precise labeling protocols, executing accurate 3D sensor data annotation, and conducting thorough quality control on all generated datasets. You will partner closely with Annotation Operations, Perception, and Engineering teams to ensure data readiness for model training and evaluation. The ideal candidate is data-driven, detail-oriented, and execution-focused, with a strong understanding of annotation workflows and a passion for improving data quality and efficiency at scale. This role plays a critical part in enabling informed decision-making, continuous process improvement, and scalable annotation operations across internal teams and external vendors.

Requirements

BS degree in a technical or related field with 2+ years of relevant experience (or 5+ years equivalent industry experience).
2+ years supporting data annotation, ML data, or labeling-related projects.
Strong understanding of 2D/3D data annotation workflows for ML and Perception use cases.
Experience with error taxonomy development and quality assurance (QA) frameworks for data annotation.
Working knowledge of databases and/or data visualization tools.
Experience analyzing LiDAR point clouds, video, and image annotation data.
Ability to manage multiple projects, prioritize effectively, and deliver under tight timelines.
Strong written and verbal communication skills, with the ability to explain project insights to non-technical stakeholders.
Experience mentoring or guiding junior team members or offshore teams.

Nice To Haves

Experience building or improving operational analytics for efficiency, cost, or quality.
Comfort working in a fast-paced, cross-functional, and collaborative environment.
Hands-on experience with data analysis, metrics tracking, and dashboarding.

Responsibilities

Analyze large-scale 2D/3D annotation datasets to identify data gaps, quality issues, coverage gaps, and inefficiencies impacting Perception and ML training.
Utilize dashboards and reports to monitor annotation throughput, efficiency, and cost, quality metrics (QA pass rates, error types, rework), and vendor and annotator performance trends.
Interpret complex annotation and perception data into clear, actionable insights for engineering, annotation operations, and leadership.
Partner with Perception teams to align data readiness metrics with model training and evaluation needs.
Effectively communicate data findings to business partners, bridging the gap between technical data and strategic organizational goals.
Assess the level of effort for annotation projects and support end-to-end execution, including in-house vs. vendor decisions.
Collaborate with stakeholders to gather labeling requirements and define, maintain, and evolve labeling policies.
Manage relationships with various vendors, including contract and quote review, for third-party annotation services and tools.
Define and track annotation quality, productivity, and certification metrics; continuously refine benchmarks.
Conduct QA/QC analysis on annotated data, identify systemic issues, and provide structured feedback to annotators and vendors.
Implement and measure labeling efficiency improvements, using data to validate impact.
Prepare technical reports and collaborate with cross-functional engineering teams to ensure consistent process implementation, with the ability to automate basic processes.
Identify opportunities to make data delivery and annotation workflows faster, more accurate, and scalable.
Identify and propose enhancements to address deficiencies in existing tooling, improving the efficiency and accuracy of annotation workflows.
Work closely with Annotation Ops, Perception, and Engineering teams to ensure consistent process implementation.
Support vendor management by analyzing performance, cost, and quality metrics across multiple annotation partners.
Prepare technical and operational reports to support planning, execution, and decision-making.
Coordinate across teams and time zones to ensure alignment and timely delivery.