Senior / Staff Software Engineer, ML Datasets & Data Pipelines

As a Senior/Staff Software Engineer embedded within our Autonomy & Algorithms team, you will build the scalable ML data pipelines necessary to train and evaluate Waabi’s autonomous driving platform. Working closely with world-renowned scientists and engineers, you will solve complex data challenges to accelerate our launch of fully driverless vehicles.

You Will..

• Design and implement data pipelines using real-world drivingdata and Waabi World (our high-fidelity simulator) to train and evaluate deep learning models.
• Optimize data formats, caching, and dataloading to drive highly efficient ML training and evaluation at scale.
• Improve data sampling and composition for deep data introspection to track model performance and uncover critical edge-case scenarios.
• Champion engineering excellence by writing high-quality, well-structured, and rigorously tested code.
• Help drive project roadmap planning, prioritization, and delivery.

Qualifications:

• BS or MS in Computer Science, Machine Learning, or a related technical field, with 4+ years of industry experience.
• Proficiency in Python and strong software engineering fundamentals, including experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Hands-on experience building distributed ETL and data processing pipelines.
• Direct experience managing ML pipelines, including dataset management, dataloading, and optimization.
• Strong understanding of cloud job orchestration, monitoring, and instrumentation best practices.
• A collaborative, open-minded approach with a passion for tackling hard problems in autonomous technology and a strong willingness to mentor others.

Bonus Points:

• Experience with optimizing large scale distributed training pipelines and/or highly optimized ML inference pipelines.
• Experience with MapReduce (Apache Hadoop/Spark) or orchestration frameworks (Apache Airflow, Apache Beam, Google Cloud Dataflow, AWS Step Functions).
• Experience solving data challenges specific to autonomous driving.
• Familiarity with linear algebra (projections, transforms) and 3D geometry.
• Experience working with multimodal sensor data (e.g., LiDAR, RADAR, camera).