Top Senior Machine Learning Jobs in NYC, NY

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

As a Senior Machine Learning Engineer, you will build intelligent search experiences that leverage machine learning for domain name suggestions, focusing on retrieval and ranking systems.

Lead and grow high-performing machine learning teams, define strategies, oversee projects, and integrate AI/ML into products while mentoring team members.

As a Staff Machine Learning Engineer, you will develop and maintain ML models for decision-making, optimize pipelines, and collaborate with a diverse engineering team.

Lead the SDL and Cash Line ML teams, developing innovative machine learning models to improve lending solutions and expand credit access. Collaborate with cross-functional teams to drive product strategy and enhance model performance, while mentoring a team of ML scientists.

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

Lead AI/machine learning innovations and advanced analytics for new vehicles. Develop statistical models for pricing and valuation, guiding experiments and communicating insights.

Responsible for designing, building, and maintaining machine learning models in production, collaborating with cross-functional teams and ensuring best practices in ML engineering.

The role involves designing, building, and deploying machine learning models and systems, while collaborating with cross-functional teams to solve business problems.

As a Senior Machine Learning Engineer at Capital One, you'll design, build, and deploy ML models, collaborate in Agile teams, and ensure the performance of ML applications. Responsibilities include model training, monitoring, and optimization in cloud-based environments.

The Machine Learning Engineer will build and deploy ML models, applying modern techniques to solve problems and collaborate with teams on ML-driven features.

Lead and support a team of engineers to build recommendation systems, guiding technical direction and collaboration for impactful music discovery at Spotify.

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

As a Senior AI Engineer, you'll develop and deploy innovative AI solutions for the fashion industry, collaborate with cross-functional teams, and refine machine learning models to enhance product offerings.

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.

The Senior Machine Learning Engineer will develop foundational models for recommendations, mentor engineers, and collaborate on improving user experiences with machine learning.

The role involves designing ML models, research, improving ML capabilities, mentoring engineers, and managing data at scale utilizing cloud platforms.

The role involves designing and implementing reinforcement learning pipelines for AI systems, integrating organizational data, and collaborating with product teams to enhance AI functionalities.

As a Sr Lead Machine Learning Engineer, you'll design, develop, and implement machine learning applications, collaborating with cross-functional teams and ensuring high performance and governance of ML systems.

As a Senior Lead Machine Learning Engineer, you'll design and implement ML systems, collaborate with cross-functional teams, and ensure high performance and governance of applications at scale.

Develop and improve machine learning models and systems for clinical outcomes. Lead ML initiatives, mentor teams, and establish best practices in AI. Collaborate across engineering, product, and design for data-driven solutions.

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

The Principal Software Engineer II will build and maintain machine learning components in Elasticsearch, collaborating with teams, writing scalable code, and owning projects from design to implementation.