Key skills
PythonPyTorchTensorFlowJAXDistributed ETL pipelinesData processing pipelinesML pipelinesDataset managementDataloadingCloud job orchestrationMonitoringInstrumentationMapReduceApache HadoopApache SparkApache AirflowApache BeamGoogle Cloud DataflowAWS Step FunctionsLinear algebra3D geometryMultimodal sensor dataLiDARRADARCameraAIMachine LearningMLDeep LearningETLSparkAirflowHadoopAWSGoogle CloudCaching
About this role
Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. 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.
Responsibilities:
- Design and implement data pipelines using real-world driving data 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
Requirements:
- 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
- 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)