Data and ML Infrastructure Engineer

Job description

Job responsibilities

• Built reliable pipelines that move operational data from field capture into organized and searchable storage.
• Made HavocAI’s video, telemetry, and sensor data significantly easier for engineers to discover and use.
• Established reproducible workflows for creating high-quality datasets for model training, evaluation, and regression testing.
• Improved data quality, lineage, metadata, and observability across critical pipelines.
• Enabled Autonomy and Perception teams to move more quickly from field data → insight → dataset → model improvement → deployment.

Job requirements

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, Electrical Engineering, Computer Engineering, Robotics, Applied Mathematics, or a related technical field.
• 3+ years of experience in data engineering, ML infrastructure, data platforms, backend systems, MLOps, or related engineering roles.
• Experience designing and operating production data pipelines for large-scale structured, semi-structured, or unstructured datasets.
• Experience supporting defense, robotics, autonomy, aerospace, or dual-use technology programs
• Experience working with video, imagery, time-series telemetry, sensor data, logs, or other high-volume operational data.
• Strong programming skills in Python and SQL.
• Experience with cloud storage, object stores, data lakes, databases, distributed processing, or modern data platforms.
• Familiarity with dataset versioning, metadata management, data lineage, access controls, and reproducible data workflows.