Senior Software Engineer, Data Mining

Summary

Join Motional's Data Mining team as a Data Engineer and spearhead new mining strategies and workflows to improve the performance of our autonomous driving ML products. You will develop data products using foundation models, own large-scale mining workflows, build high-quality datasets, and contribute to data processing pipelines. This role requires a BS in computer science or a related field, 3+ years of experience with high-performance distributed systems, and experience with VLMs or large-scale vision encoders. Fluency in Python and experience in production-quality software development are essential. Motional offers a competitive salary, benefits including medical, dental, vision, 401k, and more. The role offers the opportunity to work on cutting-edge technology and contribute to the advancement of autonomous driving.

Requirements

• BS in computer science, similar discipline or equivalent experience
• 3+ years of experience architecting and shipping high-performance & large-scale distributed systems
• Experience with deploying vision language models (VLMs) or large-scale vision encoders (e.g. CLIP) in production settings for image/video understanding, object detection or searching
• Experience with core cloud services (e.g. AWS’s S3, Athena, RDS or similar) and modern vector databases (OpenSearch, Weaviate, Pinecone etc.)
• Solid software engineering principles – such as software design patterns, configuration management, source control, build processes, code reviews, testing methodologies, app containerization, continuous integration etc
• Fluency in Python and experience on production-quality software development

Responsibilities

• Develop data products utilizing foundation models such as multi-modal encoding models (CLIP-style models), vision language models (VLMs) and large language models (LLMs) and adapt them to the autonomous driving domain via pre-training, fine-tuning and prompt optimization
• 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

Preferred Qualifications

• 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 PyTorch or other deep learning frameworks (Jax, Tensorflow etc.)
• 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.)

Benefits

• Medical
• Dental
• Vision
• 401k with a company match
• Health saving accounts
• Life insurance
• Pet insurance