Top Senior Machine Learning Jobs in NYC, NY

The role involves collaborating across departments to build AI-driven models, optimizing data for decision support, and developing scalable solutions for business growth.

The Machine Learning Engineer will design, build, and deploy ML applications at scale, collaborating with cross-functional teams and applying best practices in ML engineering and cloud technologies.

Lead a team of Machine Learning Engineers in designing, building, and implementing ML applications, focusing on data-intensive solutions and infrastructure decisions, while promoting best practices in AI.

The Lead Machine Learning Engineer will manage AI/ML project lifecycles, collaborate with teams on model optimizations, implement best practices in MLOps, and mentor juniors while ensuring model reliability.

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.

Lead the design and deployment of machine learning models for personalized navigation and recommendations, managing projects end-to-end with a focus on user-centric solutions.

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.

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

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

As a Senior Machine Learning Engineer, you will own ML infrastructure and data systems, scaling them for large volumes of video data and supporting deep learning training and experimentation.

Develop and maintain a full-stack platform for computational chemists, focusing on drug discovery through machine learning and data infrastructure. Collaborate with interdisciplinary teams to enhance software tools for visualizing molecules and managing workflows.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Design, train, and evaluate machine learning models to match patients with therapists, improving clinical outcomes and enabling tailored care.

As a Senior Machine Learning Software Engineer, you will design, deploy, and optimize ML solutions in healthcare, working with AI scientists and ensuring compliance with regulations.

Lead the Applied Machine Learning team at ExtraHop to develop systems for behavioral detection in network security. Manage model design, evaluation, and operationalization while maintaining experimental rigor and collaborating with product teams.

The role involves designing and refining reward signals for recommendations, collaborating with teams, and implementing ML solutions to enhance user satisfaction.

As a Senior Machine Learning Engineer, you'll develop and productionize ML models, design data pipelines, and ensure the scalability of features for over 200 million users, collaborating with various teams to enhance user experience.

Design, develop, and deploy scalable ML software systems for healthcare. Collaborate with teams to improve products and ensure performance and reliability.

Design and develop scalable ML systems for healthcare, collaborating with teams to enhance products and maintain efficient infrastructures.

The role involves creating models for machine learning accelerators, analyzing workloads, and collaborating with engineering teams to optimize performance and functionality.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Principal Machine Learning Engineer will design and scale ML systems for personalization and search, mentor engineers, and lead major ML initiatives at Fetch.