Infrastructure Engineer

• Implement, optimize, and maintain post-processing code that runs directly on Mobileye's target chips (primarily in C++).
• Develop and maintain critical ML infrastructure to accelerate the research team's workflow.
• Build and manage robust data processing pipelines (ETLs) for large-scale autonomous driving datasets.
• Create performance analysis tools and optimize deep learning training processes.

ML Software Engineer building software for autonomous vehicles

ML Software & Infrastructure Engineer – Student Position

ML Software Engineer in Mobileye's Hawkeye team developing software for autonomous vehicle perception. Involves building infrastructure linking research with production for safe automotive systems.

• Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.
• Build and scale the backend systems that support high-throughput document processing and data extraction workloads.
• Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.
• Own containerization and orchestration (Docker, Kubernetes) for all production workloads.
• Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.
• Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.
• Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).
• Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.
• Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.
• Build observability and monitoring systems to track infrastructure health, performance, and cost.
• Collaborate with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.
• Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

Backend Engineer specializing in infrastructure for AI-driven complex workflows

Software Engineer – Infrastructure

Backend Engineer specializing in infrastructure for AI-driven complex workflows at an early-stage startup. Focus on building and scaling infrastructure that powers autonomous AI agents.

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ML Software & Infrastructure Engineer – Student Position

Software Engineer – Infrastructure