Machine Learning Infra Engineer

@ MLabs

About the Role

MLabs is a high-growth, venture-backed defense tech company working at the cutting edge of signal processing, machine learning, and embedded systems. As a Machine Learning Infra Engineer, you will design and build core infrastructure from scratch to handle petabytes of radio spectrum data. This is a high-ownership role for an experienced engineer who values tooling best practices and future-proof architectural decisions.

What You'll Do

You will:

• Scale distributed data storage and write Python APIs for massive datasets.
• Set up orchestration for model training on GPU clusters with versioning and deployment.
• Explore innovative methods combining relational and vector-based search queries.
• Define major areas of the engineering roadmap and collaborate with researchers.

What Our Client is Looking For

Qualifications include:

• 2-7 years of experience in ML Ops and building production platforms.
• Experience in designing and implementing data infrastructure from scratch.
• Strong AWS experience including S3, Sagemaker, RDS, ECS, Lambda, and AWS CDK.
• Proven experience managing production-grade Python codebases.
• Expertise with ML experiment tracking, model versioning, and artifact deployment such as MLflow.
• U.S. Citizenship required due to defense/ITAR regulations.

Additional Details

This is a full-time on-site role based in New York, NY (Flatiron District) with relocation support available for strong candidates. Salary is competitive and includes equity. Note that visa sponsorship is not available.

Key skills/competency

• Machine Learning
• Infra Engineering
• Python
• ML Ops
• AWS
• Data Infrastructure
• Distributed Systems
• GPU Clusters
• MLflow
• Orchestration