Lead Data Platform Engineer

This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$/yr - $/yr

• Annual Bonus
• Direct message the job poster from Harnham

Lead the architecture and development of a high‑performance compute platform that powers Simulation and ML engineering teams. This role combines deep technical hands‑on work with engineering leadership, requiring expertise in distributed computing frameworks and data processing at scale.

• Design, build, and scale a user‑friendly compute platform supporting Simulation and ML workflows across the organization
• Lead architecture design and development of distributed data processing infrastructures, balancing performance and cost optimization
• Drive technical direction for infrastructure engineering, establishing coding best practices and system design patterns
• Manage and mentor an infrastructure engineering team while remaining deeply hands‑on in implementation and troubleshooting
• Optimize distributed computing frameworks for cost and performance, ensuring efficient resource utilization at scale
• Collaborate cross‑functionally with Simulation, ML, and Product teams to translate requirements into scalable infrastructure solutions
• Build and maintain CI/CD pipelines, monitoring systems, and observability tools for platform reliability

• 5+ years of professional software engineering experience with production‑level distributed systems
• Extensive experience in Python and C++ for building high‑performance data processing pipelines
• Deep hands‑on experience with distributed computing frameworks (e.g., Spark, Ray, Dask, Kubernetes, or similar)
• Proven track record optimizing cost and performance within large‑scale compute environments
• Technical leadership experience: architecture design, code reviews, mentoring engineers, and setting engineering standards
• Experience building and scaling data processing infrastructures that support ML training, simulation, or analytics workloads
• Demonstrated ability to lead engineering teams while maintaining significant hands‑on contributions to the codebase

• Experience working with sensor data pipelines (e.g., LiDAR, camera, radar) or robotics data workflows
• Background in autonomous systems, robotics, or related compute‑intensive domains
• Familiarity with GPU optimization and accelerated computing frameworks

Seniority level: Mid‑Senior level

Employment type: Full‑time

Job function: Engineering and Analyst

Industries: Robotics Engineering and Technology, Information and Media

• Medical insurance
• Vision insurance
• 401(k)
• Pension plan

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