3 months ago
Base Salary
$140k - $200k/yr
Responsibilities
- Design and develop cloud infrastructure, storage systems, and automated testing frameworks for AI training datasets and machine learning pipelines.
- Own data infrastructure from prototype architecture through data quality validation and production-scale release.
- Architect and validate data lakehouse or warehouse systems, feature stores, and automated data governance frameworks.
- Build sensor-data ingestion, model/data/label versioning, cloud orchestration, and high-throughput pipeline architectures with software and machine learning engineers.
- Develop automated data validation scripts, core ETL pipelines, infrastructure-as-code, and regression testing suites.
- Support deployments, architectural iteration, and root-cause analysis for data corruption, pipeline bottlenecks, and infrastructure failures.
- Integrate data tooling, automated labeling workflows, and third-party vendor services.
- Contribute to pilot data deployments and field telemetry loops.
- Build or support active learning pipelines, continuous training infrastructure, automated data curation systems, and GPU cloud inference services.
Requirements
- 8+ years of experience designing, building, and validating scalable cloud infrastructure and data pipelines.
- Experience building and testing enterprise-grade data systems that process massive, unstructured datasets at production scale.
- Extensive knowledge of modern data infrastructure, cloud platforms, and data quality validation frameworks.
- Experience taking at least one core data platform from initial prototype through production release and supporting its long-term stability.
- Preferred experience with autonomy, robotics, industrial equipment, or automotive data loops involving multimodal vehicle telemetry and sensor data.
- Preferred experience with data governance, safety-critical data validation frameworks, or compliance standards for autonomous systems.
- Preferred experience deploying and optimizing GPU cloud inference services using NVIDIA architecture, including Triton.
- Preferred experience collaborating with internal and third-party data-labeling services and external annotation integrations.
Benefits
- The role may be eligible for equity and benefits.
- Base pay depends on skills, work experience, location, and qualifications, with a listed range of $140,000-$200,000 per year.
Categories
Data EngineeringTesting
About Ouster
Ouster builds digital lidar sensors and perception software used by automotive, industrial, robotics, and smart infrastructure customers. The company sells hardware and software to OEMs and system integrators, with a portfolio spanning high‑resolution lidar and sensor‑fusion tools. Founded in 2015 and headquartered in San Francisco, Ouster is publicly traded (ticker: OUST) and merged with Velodyne Lidar in 2023 to expand its product lineup and customer base.