Senior Machine Learning Infra Engineer

Summary

Join Waabi, a leading AI company revolutionizing self-driving technology, and contribute to building the next generation of safe and scalable autonomous vehicles. Work alongside a team of expert engineers and researchers using an AI-first approach. Collaborate with cross-functional teams to design and implement robust cloud infrastructure for training and simulation workloads. Develop and implement cloud strategies, ensuring optimal performance and reliability. Waabi offers a competitive salary, comprehensive benefits, and a dynamic work environment. We are seeking highly skilled and passionate individuals to join our growing team and make a significant impact on the future of transportation.

Requirements

• BS, MS/PhD in Computer Science or similar technical field of study or equivalent practical experience
• 5+ years of relevant industry experience
• Experience in reading and developing production quality software
• Deep understanding of Cloud compute and data storage for distributed training and inference workloads
• Familiarity with Python, GO, Rust or C++ ecosystems
• Experience working with public cloud platforms (AWS preferred)
• Experience with infrastructure as code systems (Terraform preferred)
• Experience in job scheduling and resource allocation
• Experience with containers and container orchestration (i.e., Docker, ECS, Kubernetes)
• Experience and high level of comfort working with Linux systems
• Experience with building platform services that enable other teams to do their best work
• Open-minded and collaborative team player with the willingness to help others
• Passionate about self-driving technologies, solving hard problems, and creating innovative solutions
• Experience working in an Agile/Scrum environment

Responsibilities

• Work alongside a team of multidisciplinary Engineers and Research Scientists using an AI-first approach to enable safe self-driving at scale
• Collaborate with cross-functional teams in the company to understand the growing need and pain points in cloud usage
• Propose cloud strategies around compute and data usages for training and simulation workloads
• Design and implement scalable and resilient cloud infrastructure optimized for long term reliability and adaptability
• Devise and promote best practices for cloud usages in training and simulation environments, oversee cloud strategies and usages across the whole company

Preferred Qualifications

• Experience with on-premise servers, network equipment and scale-out storage systems
• Experience with CI/CD pipelines and release management
• Experience in common ML tools, workflows and frameworks (i.e. systems like Kubeflow or MLFlow)
• Understand system performance tuning at software, hardware, and network levels
• Have good understanding of GPUs and accelerators in ML training and inference use cases

Benefits

• Competitive compensation and equity awards
• Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only)
• Unlimited Vacation
• Flexible hours and Work from Home support
• Daily drinks, snacks and catered meals (when in office)
• Regularly scheduled team building activities and social events both on-site, off-site & virtually