Lead Machine Learning Infrastructure Engineer

$160,000 - $210,000/Yr

Cobalt AI, LLC - San Francisco, CA

Full-time - Mid Level

Remote - San Francisco, CA

About the position

The Lead Machine Learning Infrastructure Engineer at Cobalt AI will play a crucial role in designing and implementing robust machine learning pipelines for processing large volumes of video streams. This position focuses on enhancing the performance and reliability of GPU workloads, both on edge devices and in the cloud, while also integrating cutting-edge computer vision models to improve decision-making in security contexts. The role involves leading a team of engineers, establishing best practices, and tackling complex interdisciplinary challenges within the company's deep tech stack.

Responsibilities

• Design and implement robust machine learning pipelines to process multiple video streams simultaneously.
• Improve the performance and reliability of GPU workloads on edge devices and in the cloud.
• Design and implement scalable infrastructure for deploying CUDA-enabled ML models to edge devices.
• Discover, evaluate, and integrate advanced computer vision models and algorithms for time-sensitive decision making.
• Assess and address networking and data storage security risks for edge processors and their backend integration.
• Lead a team of senior and junior engineers, establishing best practices in ML infrastructure development.
• Conduct design reviews and gather input from various teams to ensure high-quality outcomes.
• Solve challenging interdisciplinary problems within the deep tech stack.
• Deploy changes that have immediate impacts on the product globally.

Requirements

• Minimum 5+ years of experience in software engineering with a focus on ML infrastructure design.
• Experience leading teams or managing projects.
• Demonstrated expertise in ML infrastructure development and best coding practices for Python, C++, Rust, or equivalent.
• Experience with pipeline stability and resilience using tools like Datadog or equivalent.
• Passionate about delivering high-quality products that exceed user expectations.
• Eager to work with, mentor, and learn from peers through code reviews, design documents, and pair programming.
• Enthusiastic about exploring different areas of technology and problem-solving.
• Must be authorized to work in the United States.

Nice-to-haves

• Experience with generative AI technologies.
• Experience with event streams, like Kinesis or equivalent.
• Familiarity with the Nix package manager and its ecosystem.
• Experience working in a fast-paced startup environment.
• Hands-on experience with AWS and DevOps practices.
• Expertise in networking and security protocols.
• Experience building and scaling high availability distributed systems.
• Background as a full-stack engineer.

Benefits

• Remote work
• Professional development opportunities
• Work-life balance
• Empathetic workplace culture