Software Engineer, Data Platform – Autonomous Vehicles

• Design & develop the next generation distributed ML data platform (Ingestion, Processing, Serving) using GCP and open-source frameworks
• Collaborate with stakeholders (ML & Data Engineers), translate needs & pain points into requirements, build self-serve capabilities and drive adoption
• Deliver technical projects owning major technical decisions and tradeoffs & contribute to the team’s strategic roadmap
• Champion engineering & operational excellence by continuously improving systems and processes
• Actively participate in team’s planning, code reviews and design discussions
• Conduct technical interviews, onboard new and mentor junior engineers

• BA or BS in Computer Science, Electrical Engineering, Mathematics, Physics, or another relevant field; or equivalent real-world experience
• 3+ years in building petabyte-scale distributed data platforms, specifically evolving Data Lakes into Lake houses using major cloud providers and open-source frameworks
• Expert-level proficiency in Java, C++, or Python , with a proven track record of designing and implementing robust, distributed systems
• Expertise in implementing Data Processing Frameworks (Beam, Spark) and serving layers optimized for high-throughput, low-latency delivery
• Experience optimizing services for cost efficiency, performance & reliability
• Experience with Micro services architecture and proven ability to manage the full operational lifecycle of systems

Demonstrates expertise in designing and developing distributed ML data platforms using GCP and open-source frameworks, with a strong focus on data processing frameworks and microservices architecture. Proven ability to mentor junior engineers and drive technical projects while optimizing for performance and cost efficiency.

• Distributed Data Platform Development
• Expert-Level Proficiency in Java, C++, or Python
• Data Processing Frameworks (Beam, Spark)
• Microservices Architecture
• Technical Project Ownership

• Distributed Systems Design
• Data Lake to Lakehouse Evolution
• High-Throughput, Low-Latency Optimization
• Cost Efficiency Optimization
• Operational Lifecycle Management

• Collaboration with Stakeholders
• Mentoring Junior Engineers
• Technical Interviewing

• Data Engineering
• Machine Learning
• Data Processing
• Cloud Computing

• GCP
• Open-Source Frameworks
• Microservices