Senior Software Engineer, Data Mining - Continuous Learning

Mission Summary:

At Motional, data play a critical role in fueling our ML-centered autonomous driving vehicle. Our robo-taxi fleet collects petabytes of data on the road every day – the Data Mining team is mining & filtering the massive influx of fleet data by developing billion-scale data workflows and state-of-the-art mining algorithms. Through our Continuous Learning Framework we continuously improve the on-road performance of ML products for perception, prediction & planning with every mile driven.

We mine for model errors, anomalies, rare objects & long-tail driving scenarios across millions of driving hours – these are used for laser-focused ML model training and continuous edge case validation. We are looking for an engineer to spearhead new mining strategies & workflows and help deliver high-quality data that improve our core ML products.

Read more about Continuous Learning and Data Mining at Motional:

• Continuous Learning Framework
• Scenario Mining

What you'll be doing: 

• Own large-scale mining workflows that surface rare objects, model errors & long-tail events.
• Build high-quality datasets to improve ML products through training & edge case validation.
• Contribute to data processing pipelines that fuel our in-house billion-scale image search engine.
• Provide statistical depth on model performance & generalization through rigorous error analysis across complex driving scenarios.

What we're looking for:

• BS in computer science or similar discipline.
• 5+ years of experience architecting and shipping high-performance & large-scale distributed systems.
• Experience with core AWS services (S3, RDS, EMR, EKS, OpenSearch etc.).
• Experience with writing complex yet efficient SQL queries for data analysis purposes.
• Experience with common DBMS (PostgreSQL, MySQL, MongoDB etc.).
• Experience with data warehousing and parquet data manipulation (e.g. Athena, Redshift, BigQuery).
• Experience with Spark, Beam, Kafka, Hadoop or other data processing tools.
• Fluency in Python and experience on production-quality software development.
• Solid software engineering principles (software design patterns, configuration management, source control, build processes, code reviews, testing methodologies, app containerization, continuous integration etc.).

Bonus Points (not required):

• MS/PhD in computer science, machine learning, statistics or computer vision.
• Experience with at least one of the following ML techniques/models: Few-shot Learning, Metric Learning, Information Retrieval, Recommender Systems, Contrastive Learning, Semi-supervised Learning, Object Detection / Segmentation / Prediction.
• Experience with data visualization tools (Redash, Looker, PowerBI, Tableau etc.).
• Experience with PyTorch or other deep learning frameworks.
• Experience with A/B testing methodologies and metrics tracking systems.
• Experience with machine learning in the autonomous driving domain.
• Familiarity with autonomous driving sensors (cameras, lidar, radar, localization sensors etc.).

This position can support remote work within the United States.