MTS: Data Infrastructure

Essential AI’s mission is to deepen the partnership between humans and computers, unlocking collaborative capabilities that far exceed what could be achieved today. We believe that building delightful end-user experiences requires innovating across the stack – from the UX all the way down to models that achieve the best user value per FLOP.

We believe that a small, focused team of motivated individuals can create outsized breakthroughs. We are building a world-class multi-disciplinary team who are excited to solve hard real-world AI problems. We are well-capitalized and supported by March Capital and Thrive Capital, with participation from AMD, Franklin Venture Partners, Google, KB Investment, NVIDIA.

The Role

The Data Infrastructure Engineer will design, implement, and optimize a scalable infrastructure to prepare the data that powers our AI training. This infrastructure must be reliable and capable of efficiently processing petabytes of data. You will collaborate closely with the data research team and data crawling team when designing this system.

What you will be working on

• Building petabyte-scale, high-throughput data processing systems for preparing and curating datasets for AI training.

• Orchestrating workloads across large clusters; Architecting and maintaining distributed computing environments.

• Working directly with our data research team on implementing new methods of data preparation.

• Troubleshooting and resolving infrastructure-related issues in a timely manner.

What we are looking for

• Minimum of 3 years of experience in data-intensive applications and software development.

• Proficient with Kubernetes & containerization and with building cloud services using providers like AWS, GCP etc.

• Ability to write, debug and optimize distributed systems and understanding of data orchestration and automation tools (or strong willingness to learn)

• Proficient in high performance programming languages like Go or Rust or C++.

• You have previous experience in creating and maintaining infrastructure for processing datasets for ML model training and/or serving

We encourage you to apply for this position even if you don’t check all of the above requirements but want to spend time pushing on these techniques.

We are based in-person in SF. We offer relocation assistance to new employees.