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Scale Ai Data Labeling Jobs (Flexible Options) in California

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Lead, Data Quality - Partnerships

San Jose, CA · On-site

$120K - $180K/yr

Experience scaling a multi-vendor or multi-region labeling operation. * Experience with golden set / ground truth construction. * Background in robotics, autonomous systems, LLM, or physical AI data.

Figure

Lead, Data Quality - Partnerships

San Jose, CA · On-site

$120K - $180K/yr

Experience scaling a multi-vendor or multi-region labeling operation. * Experience with golden set / ground truth construction. * Background in robotics, autonomous systems, LLM, or physical AI data.

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Senior AI Data Pipeline Engineer (Autonomous Driving)

42dot

Sunnyvale, CA • On-site

$123K - $168K/yr

Full-time

Re-posted 5 days ago

Job description

Job Summary:
42dot is a mobility AI company committed to solving mobility challenges with software and AI. They are seeking a Senior AI Data Pipeline Engineer to build core data processing pipelines and datasets for autonomous driving algorithms, enhancing the efficiency of the ML model development lifecycle.
Responsibilities:
• Develop high scale, reliable data extraction pipeline to extract millions of raw data from data collection fleet and convert to high-value scene data
• Develop data labeling pipelines to perform the auto labeling inferences for autonomous driving algorithms
• Develop advanced autonomous driving data SDK, including scene data search, datasets preparation, dataset loading, etc.
• Build up the data lakehouse for autonomous driving scene dataset, including the sensor data, calibration data, as well as annotation data
• Dig into performance bottlenecks all along the data processing pipelines, from data processing latency, data search latency to Test Procedure (TP) coverage.
• Bootstrap and maintain infrastructure for data platform components—data processing pipeline, database, data lakehouse and data serving.
• Collaborate with cross-functional teams, including ML algorithm, ML application, and Cloud Infra to align data pipelines with overall autonomous driving system architecture.
Qualifications:
Required:
• Bachelor's degree or higher in Computer Science, Engineering, Robotics, or a similar technical field.
• Minimum of 7 years of experience in Data Engineering, DataOps or ML Platform roles
• Proficient in Python and solid experience in Python SDK development
• Solid hands-on experience with data pipeline job orchestration with Databricks Workflows or Apache Airflow, as well as integrating data pipelines with machine learning models
• Solid working experience in Databases (e.g., MongoDB, PostgreSQL, etc)
• Extensive experience with data technologies and architectures such as Data Warehouse (e.g., Hive) or Lakehouse (e.g., Delta Lake)
• Experience with Apache Spark or other big data computing engines
• Excellent leadership and communication skills, with a demonstrated ability to lead technical projects
Preferred:
• Experience with autonomous vehicle sensor data (e.g., LiDAR, camera, radar)
• Experience with ML model training lifecycle (e.g., data preparation, model training / validation / deployment, etc)
• Understanding of modern AI frameworks (e.g., PyTorch, TensorFlow etc.)
• Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data
Company:
42dot is a mobility AI company that specializes in autonomous transportation and mobility solutions. Founded in 2019, the company is headquartered in Seoul, KOR, with a team of 501-1000 employees. The company is currently Late Stage.

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