Top Hybrid Machine Learning Engineer Jobs in New York City, NY

The Machine Learning Specialist will develop predictive models for portfolio optimization and investment analysis, ensuring rigorous testing and deployment in a cloud environment.

The Staff Machine Learning Engineer will architect and optimize data infrastructure for multimodal AI models in oncology, focusing on data management and processing pipelines.

The role focuses on developing data-driven models for optimizing catalyst materials via machine learning and quantum mechanical simulations, collaborating on catalysis research.

Build and maintain AI-powered, time-aware forecasting and pattern-discovery models for front-office rates trading. Apply statistical learning and time series techniques, productionize ML/AI models, and collaborate with trading, risk, and governance teams to integrate predictive intelligence into business processes.

The Senior Machine Learning Engineer will modernize Unity's AI systems by designing intelligent agents, developing applications, and ensuring quality through collaboration and innovation.

The Machine Learning Engineer will manage the end-to-end ML lifecycle, collaborate with cross-functional teams, develop production models, and monitor their performance in high-stakes environments.

The Staff Machine Learning Engineer will build recommendation systems, lead ML projects, collaborate with teams, and mentor junior engineers, focusing on scalable AI solutions for dating outcomes.

As a Machine Learning Engineer, you'll design and deploy large-scale models for advertising and commerce systems, optimizing for performance and relevance while maintaining ML pipelines.

Lead research and development of advanced fraud detection ML models, experiment design, productionizing prototypes, and mentoring engineers.

The Staff Software Engineer will develop and deploy high-performance machine learning systems, optimizing large language models for production environments. Responsibilities include ensuring high availability and low latency for AI applications and working collaboratively across teams.