Machine Learning Engineer

OON Systems LLC; New York (NY); Hybrid; USD 120,000 - 190,000; Full time

Job summary

OON Systems LLC is building AI-first infrastructure for complex healthcare workflows. As a Machine Learning Engineer, you will design, train, and deploy production models that improve decision quality, automate operational processes, and support real-world optimization across high-value workflows.

You will work across data pipelines, model development, evaluation, and deployment. Collaborate with product and engineering teams to move models from experimentation into production, and continuously

Qualifications

• Strong Python skills and experience with modern ML tooling.
• Strong foundation in machine learning, statistics, and production engineering.
• Ability to work across data, modeling, and deployment problems.
• Strong quantitative reasoning and problem-solving ability.

Responsibilities

• Design, train, and deploy machine learning systems for structured and unstructured healthcare workflow data
• Build scalable data pipelines for model training, evaluation, and monitoring
• Work on model optimization, feature engineering, and deployment reliability
• Collaborate with product and engineering teams to move models from experimentation into production
• Continuously improve model performance using real world outcomes and feedback loops

Skills

Python

ML tooling

Statistics

Problem solving

Data analysis

Tools

PyTorch

TensorFlow

Job description

OON Systems is building AI-first infrastructure for complex healthcare workflows. As a Machine Learning Engineer, you will design, train, and deploy production models that improve decision quality, automate operational processes, and support real-world optimization across high-value workflows.

You will work across data pipelines, model development, evaluation, and deployment.

Responsibilities

• Design, train, and deploy machine learning systems for structured and unstructured healthcare workflow data
• Build scalable data pipelines for model training, evaluation, and monitoring
• Work on model optimization, feature engineering, and deployment reliability
• Collaborate with product and engineering teams to move models from experimentation into production
• Continuously improve model performance using real world outcomes and feedback loops

Qualifications

• Strong Python skills and experience with modern ML tooling
• Experience with PyTorch, TensorFlow, or similar frameworks
• Strong foundation in machine learning, statistics, and production engineering
• Ability to work across data, modeling, and deployment problems
• Strong quantitative reasoning and problem-solving ability

About You

• Quantitatively focused
• Fast learner
• Comfortable working across messy real-world problems
• Strong attention to detail
• Able to execute quickly without sacrificing rigor