Production ML Engineer: End-to-End ML Lifecycle

Nodi; New York (NY); On-site; USD 190,000 - 245,000; Full time

Job summary

Nodi is seeking a generalist Machine Learning Engineer to turn ML research into production capabilities inside our platform. You will work with ML researchers to design experiments, build training pipelines, evaluate models, and deploy reliable services.

This hands-on role covers data preparation, training, inference, monitoring, and product integration. You must have strong software engineering fundamentals, 4+ years in ML, and be able to work on-site at the Brooklyn Navy Yard in New York.

Qualifications

• 4+ years in ML engineering, research engineering, or related software role.
• Strong Python and software engineering discipline: testing, code review, packaging, system design.
• Hands-on experience with PyTorch: training, evaluating, debugging models.
• Experience building data pipelines on cloud infrastructure, with containers and GPUs.
• Experience deploying models through services or batch pipelines with observability and cost awareness.
• Collaborates with researchers as a peer, quick to make implementation calls with moving requirements.
• Generalist with ability to traverse model code, data, infrastructure, and product integration.
• Able to work on-site at the Brooklyn Navy Yard.

Responsibilities

• Turn research ideas into working implementations with researchers.
• Build and run training pipelines for datasets, configurations, and compute efficiency.
• Make experiments reproducible with tracked code, data, and environments.
• Evaluate models for product use with datasets, tests, and evidence-based decisions.
• Deploy and integrate models into product workflows and services.
• Improve inference performance, latency, memory, and cost while maintaining quality.
• Monitor models post-release, diagnose issues, and feed learnings back to research.
• Improve how the team ships ML with shared tooling and automation.

Skills

Python

ML production

Model deployment

Observability

Cross-functional collaboration

Tools

PyTorch

Docker

Kubernetes

Job description

Nodi is seeking a generalist Machine Learning Engineer to turn ML research into production capabilities inside our platform. You will work with ML researchers to design experiments, build training pipelines, evaluate models, and deploy reliable services.

This hands-on role covers data preparation, training, inference, monitoring, and product integration. You must have strong software engineering fundamentals, 4+ years in ML, and be able to work on-site at the Brooklyn Navy Yard in New York.