Storm4
Overview
MLOps Engineer NYC - DefenseTech Base pay range : $160,000.00/yr - $220,000.00/yr $200,000 base + Equity A well-funded, venture-backed startup is building
next-generation ML systems for mission-critical applications . Were seeking an
MLOps Engineer
to design and scale the infrastructure that takes machine learning models from experiment to production in days, not weeks. Why Join Impactful Work:
See your infrastructure directly enable ML models to solve high-stakes, real-world problems. Ownership:
Lead the build-out of experiment tracking, model registry, and deployment pipelines. Growth Stage:
Join a small, rapidly scaling team where your work sets the technical foundations. Top Backing:
Supported by leading investors with strong runway and long-term vision.
What Youll Do
Develop platforms that track, package, and ship ML models into production environments. Build schemas and APIs to make datasets auditable and discoverable. Automate manual workflows into robust pipelines and developer tools. Maintain best-in-class documentation, repos, and structured engineering practices. Work hand-in-hand with ML researchers and engineers to maximize velocity.
What Were Looking For
Experience:
27 years in MLOps, ML Infrastructure, or Developer Infrastructure roles. Python as your main language, with comfort in C++ or other low-level languages. Strong AWS & Infrastructure-as-Code (S3, Lambda/ECS, CDK, networking). Hands-on with MLflow, Weights & Biases, SageMaker, or equivalent tools.
Mindset
Organized, automation-driven, and detail-oriented. Enthusiastic about tooling and infrastructure (not ML modeling itself).
Requirements
US citizens only (eligible for security clearance). Must work
in-person in New York City, 5 days/week . Generalist DevOps/cloud engineers without ML team experience. Data pipeline engineers focused only on ETL. Academic researchers without production experience. Backend engineers without ML workflow knowledge.
If youre passionate about building the backbone that enables machine learning teams to operate at full speed, this is a rare opportunity to shape infrastructure at an early stage with major impact. Seniority level Mid-Senior level
Employment type
Full-time
Job function
Information Technology and Engineering
Industries
Defense and Space Manufacturing and Software Development
Were not including additional postings or referrals details in this refined description. #J-18808-Ljbffr
MLOps Engineer NYC - DefenseTech Base pay range : $160,000.00/yr - $220,000.00/yr $200,000 base + Equity A well-funded, venture-backed startup is building
next-generation ML systems for mission-critical applications . Were seeking an
MLOps Engineer
to design and scale the infrastructure that takes machine learning models from experiment to production in days, not weeks. Why Join Impactful Work:
See your infrastructure directly enable ML models to solve high-stakes, real-world problems. Ownership:
Lead the build-out of experiment tracking, model registry, and deployment pipelines. Growth Stage:
Join a small, rapidly scaling team where your work sets the technical foundations. Top Backing:
Supported by leading investors with strong runway and long-term vision.
What Youll Do
Develop platforms that track, package, and ship ML models into production environments. Build schemas and APIs to make datasets auditable and discoverable. Automate manual workflows into robust pipelines and developer tools. Maintain best-in-class documentation, repos, and structured engineering practices. Work hand-in-hand with ML researchers and engineers to maximize velocity.
What Were Looking For
Experience:
27 years in MLOps, ML Infrastructure, or Developer Infrastructure roles. Python as your main language, with comfort in C++ or other low-level languages. Strong AWS & Infrastructure-as-Code (S3, Lambda/ECS, CDK, networking). Hands-on with MLflow, Weights & Biases, SageMaker, or equivalent tools.
Mindset
Organized, automation-driven, and detail-oriented. Enthusiastic about tooling and infrastructure (not ML modeling itself).
Requirements
US citizens only (eligible for security clearance). Must work
in-person in New York City, 5 days/week . Generalist DevOps/cloud engineers without ML team experience. Data pipeline engineers focused only on ETL. Academic researchers without production experience. Backend engineers without ML workflow knowledge.
If youre passionate about building the backbone that enables machine learning teams to operate at full speed, this is a rare opportunity to shape infrastructure at an early stage with major impact. Seniority level Mid-Senior level
Employment type
Full-time
Job function
Information Technology and Engineering
Industries
Defense and Space Manufacturing and Software Development
Were not including additional postings or referrals details in this refined description. #J-18808-Ljbffr