Required Senior Data & ML Infrastructure Engineer
What will your job look like?
Optimize distributed data and evaluation pipelines for memory efficiency, throughput, and training performance.
Build tools for data exploration, manipulation, validation, and quality assessment.
Own model manipulation, packaging, distribution workflows, and interfaces with downstream deployment and EyeQ integration.
Coordinate data contracts and workflows with researchers, infrastructure and data teams, and internal customers across.
What will your job look like?
Optimize distributed data and evaluation pipelines for memory efficiency, throughput, and training performance.
Build tools for data exploration, manipulation, validation, and quality assessment.
Own model manipulation, packaging, distribution workflows, and interfaces with downstream deployment and EyeQ integration.
Coordinate data contracts and workflows with researchers, infrastructure and data teams, and internal customers across.
Requirements:
Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or a related field from a leading university.
4+ years of hands-on software or data-engineering experience.
Excellent Python and Linux skills with strong software-engineering foundations.
Strong experience with SQL, Spark, and PyArrow.
Experience optimizing distributed pipelines or compute-intensive systems for memory use and parallel execution.
Familiarity with PyTorch and ML workflows, including datasets, training, checkpoints, evaluation, and GPU computation.
Strong ownership, independent problem-solving, and cross-team collaboration skills.
Master's degree in a relevant field.
Experience in computer vision or autonomous-driving systems.
Familiarity with model deployment, hardware-aware ML, or specialized AI accelerators.
Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or a related field from a leading university.
4+ years of hands-on software or data-engineering experience.
Excellent Python and Linux skills with strong software-engineering foundations.
Strong experience with SQL, Spark, and PyArrow.
Experience optimizing distributed pipelines or compute-intensive systems for memory use and parallel execution.
Familiarity with PyTorch and ML workflows, including datasets, training, checkpoints, evaluation, and GPU computation.
Strong ownership, independent problem-solving, and cross-team collaboration skills.
Master's degree in a relevant field.
Experience in computer vision or autonomous-driving systems.
Familiarity with model deployment, hardware-aware ML, or specialized AI accelerators.
This position is open to all candidates.
