What makes radar powerful - its long wavelength which makes it robust to all sorts of weather and lighting conditions - also makes it really challenging to work with. We have used our deep understanding of radar physics to build radar perception models that bring a rich and complete understanding of the environment around the AV from free space to object detections to road structure. Check out what our technology can do here - all produced with only radar information, no camera and no lidar!

Zendar has a diverse and dynamic team of hardware, machine learning, signal processing and software engineers with a deep background in sensing technology. We have a global team of 60, distributed across our sites in Berkeley, Lindau (Germany), and Paris.

Zendar is backed by Tier-1 VCs, has raised more than $50M in funding and has established strong partnerships with industry leaders.

Who You Are To support our growing team, we’re looking for a Senior Data Engineer to elevate our processes and technologies to the next level. If you are excited about designing and managing the complex signal processing data engineering pipelines, we’d love to hear from you!

We have a rapidly growing corpus of driving data, encompassing tens of thousands of kilometers of real-world driving on three continents, and a total data size of multiple petabytes. We add to that on a daily basis with data coming from our fleet of data collection vehicles. The Data team is responsible for indexing, processing, and categorizing all this data so that we make it frictionless to use it to test, train, and improve our driving models. Your responsibilities will focus on developing ETL data pipelines to guarantee data quality and to extract rich insights about the data that are available for downstream use. Some examples of data insights include categorizing driving behaviors, environments, and road user types. Our ETL pipelines are not your typical pipelines - they are robotics tasks such as vehicle calibration, driving behavior analysis, and video understanding models.

You will be based in our Berkeley site but join a Data Engineering team which is distributed between Berkeley and Europe. As the 6th member of the Data team and the 3rd in Berkeley, you will have a lot of visibility and responsibility within the team. This type of environment is perfect for someone who is comfortable managing multiple responsibilities simultaneously, enjoys interacting frequently with other engineers, and is opinionated about what to prioritize and how to build things.

Key Responsibilities ML Data Management:

• 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

Support For ML Engineers

• Serve as liaison to support Berkeley, Paris & German office ML engineers (Human annotation processing, data calibration, data upload issues)

Setting And Maintaining Infrastructure Standards

• Be a go-to resource for solving infrastructure-related challenges, fostering a culture of ownership and accountability in the team.

What We’re Looking For

• 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.

Bonus Points

• 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.

What You Would Work On

• 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.

What We Have To Offer

• Opportunity to make an impact at a young, venture-backed company in an emerging market
• Collaboration with smart and motivated engineers and ability to execute your vision in a high impact role
• Competitive salary and benefits

*Zendar is committed to creating a diverse environment where talented people come to do their best work. We are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

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