Top Senior Machine Learning Jobs in NYC, NY

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

Lead the development of production-grade ML systems, aligning technical roadmaps with company priorities, mentoring ML engineers, and ensuring ethical use of ML/AI.

Design and build AI-powered consumer products, partner with cross-functional teams, and lead the development of machine learning systems.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

Lead the design, execution, and analysis of machine learning-driven product experiments to optimize ordering systems. Collaborate with stakeholders and mentor teams.

Lead the design and deployment of machine learning models for personalized navigation, collaborate across teams, and drive technical excellence in ML practices.

Design, build, and deploy AI features for claim synthesis; implement machine learning solutions and improve model performance through collaboration and evaluation.

Lead the design, development, and deployment of machine learning applications, focusing on optimizing ML models and systems in a collaborative Agile environment.

As a Machine Learning Engineer in Fraud Risk, you'll build and maintain ML systems for fraud detection and anomaly analysis, ensuring robust performance and real-time decision making.

Responsible for designing and developing AI/ML product features and infrastructure to empower intelligent business decisions and operational excellence for customers.

The Senior Machine Learning Engineer will focus on developing innovative solutions for document intelligence, utilizing machine learning techniques to enhance company offerings.

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

As a Senior Machine Learning Engineer, you'll enhance content recommendations for millions using advanced ML models, lead AB tests, and mentor team members.

Design and build ML features using LLMs, collaborate on technical architecture, and ensure safety and performance of deployments.

Design and implement AI/ML systems for healthcare challenges, manage machine learning systems, and develop data pipelines for real-time insights.

Lead training, evaluation, and deployment of ML models for scene understanding and behavior prediction in autonomous vehicles.

You will train, evaluate, and deploy ML models for scene understanding and behavior prediction in autonomous vehicles, while collaborating with engineers.

As a Principal Engineer on the Behaviors team, you will guide the technology direction, lead complex initiatives, and mentor engineers to enhance autonomous vehicle capabilities through ML solutions.

Lead and mentor ML engineers and data scientists, overseeing ML strategy and development of scalable models for healthcare applications.

Lead the development of ML solutions to enhance user experience at Babylist. Build recommender systems and personalization features from scratch, collaborating with a cross-functional team.

Senior Software Engineer role focused on building AI capabilities for an engineering AGI product. Collaborate with a team to integrate cutting-edge machine learning into real-world engineering systems and shape product design.

The ML Researcher / Modeling Quant will design, train, and optimize ML models for trading strategies, ensuring efficient production and integration with trading operations. The role emphasizes teamwork and rapid prototyping under real trading constraints.