Senior Data Engineer/Scientist
- Maintain and grow a robust and reliable data lake in GCP for our proprietary training and evaluation data.
- Ensure robust data quality control with carefully designed algorithms.
- Grow our data lookup capabilities for data selection for labeling and model training.
- Own data quality algorithms and actively monitor data corruption in the datalake
- Serve as liaison to support Berkeley, Paris & German office ML engineers (Human annotation processing, data calibration, data upload issues)
- Be a go-to resource for solving infrastructure-related challenges, fostering a culture of ownership and accountability in the team.
- 5+ years in Data Science, MLOps or similar
- Strong algorithmic and optimization skills, especially in statistics and signal processing.
- Deep experience with cloud computing platforms (GCP or other), production-grade database design/deployment and Cloud-native ML workflow.
- Broad knowledge of data engineering and MLOps tools (Lambda, Kubernetes, Terraform).
- Proficiency with Python and SQL queries.
- A proactive approach to solving problems and willingness to take on new challenges as they arise.
- Somebody with solid opinions based on experience, yet open-minded and flexible to find the best solution for the situation.
- Ability to work from the office in Berkeley at least from Tuesday to Thursday.
- Prior experience in ADAS or sensor data processing pipelines (radar, lidar).
- Familiarity with Google BigQuery and related data visualization tools.
- Experience with production-grade serverless batch/streaming applications.
- Hands-on experience in the management of large datalakes (>1PB).
- NoSQL database design/deployment experience.
- A track record of excelling in ambiguous or evolving roles.
- When sorting through 1000s of hours of data, understanding what is in our training data is critical! Leveraging existing camera object detection models and automating data labeling is the logical next step, significantly reducing manual effort and streamlining the data pipeline. As the research requirements change, the camera model integration needs to seamlessly adjust as well.
- Sensors and vehicle calibrations can drift unexpectedly, which if undetected significantly harms the quality of results. We need to automatically identify calibration drifts and correct them before data is consumed, so that data users can have high trust in the quality of the data they work with.
- Enriching our ground truth data with KPIs designed by the Product and push them to production.
- Our signal processing pipelines are using hundreds/thousands of VM hours, the monitoring of their performance can be tricky, enhancing our tooling is essential to select the next candidate for cost optimisation.
- Opportunity to make an impact at a young, venture-backed company in an emerging market
- Competitive salary ranging from $150,000 to $190,000 annually depending on experience
- Performance based Bonus
- Benefits including medical, dental, and vision insurance, flexible PTO, and equity
- Hybrid work model: in office 3 days per week from Tuesday to Thursday, the rest… work from wherever!
- Daily catered lunch and a stocked fridge (when working out of the Berkeley, CA office)
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