Top Machine Learning Jobs in NYC, NY

The role involves designing and implementing machine learning applications, managing teams, ensuring performance, and optimizing ML systems using cloud technologies and best practices.

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

As a Senior Machine Learning Engineer, you will develop machine learning models, manage their lifecycle, build infrastructure, and collaborate with teams to enhance our capabilities in various ML areas.

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 establishing the technical vision for personalization, solving complex ML challenges, architecting solutions, and influencing strategy across teams.

The Principal ML Engineer will establish the technical vision for personalization at Launch Potato, addressing complex ML challenges and leading cross-functional initiatives.

Drive personalization strategy and architecture at Launch Potato, solving complex ML challenges and mentoring senior engineers while advancing company KPIs through innovative solutions.

Lead ML strategy and architecture at Launch Potato, focusing on personalization challenges, mentoring teams, and driving business impact through innovative solutions.

As a Principal Machine Learning Engineer, you will design ML architecture, solve technical challenges, mentor engineers, and represent the company externally.

Lead a team of ML engineers to build advanced personalization systems, balancing technical work with leadership, mentorship, and collaboration across teams.

Lead a team of ML engineers to architect and improve personalization systems, overseeing both technical work and team leadership while collaborating across organizations.

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.

The role involves developing ML models and data pipelines, working with simulation engineers, and improving engineering practices in an AI-focused environment.

As a Machine Learning Engineer, you'll design and ship LLM-based solutions, collaborate across teams, and improve storytelling capabilities at scale.

As a VP Applied AI/ML Scientist, you will develop and implement machine learning models to enhance payment processes, fraud detection, and customer experience, while collaborating with cross-functional teams.

Seeking an experienced Lead Machine Learning Engineer to manage AI/ML projects, enhance ad-serving platforms, and mentor junior team members.

Develop AI-based search and classification products for programmatic advertising. Design ML solutions for transforming data and enhancing targeting strategies using big data analytics.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

The role involves developing ML techniques for code security, training models, building evaluation pipelines, and collaborating on research innovations.

As a Staff Machine Learning Engineer, you will lead the design, implementation, and optimization of machine learning models, collaborate cross-functionally, and drive AI strategy to enhance SailPoint's identity security solutions.

The role involves designing and building ML models, managing teams, optimizing ML systems, and implementing cloud-based architectures. Collaboration with product and data science teams is crucial.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

As a Machine Learning Intern, you will lead projects, analyze data, build models, and solve complex problems using machine learning and AI techniques.

Design, implement, and improve components in a machine learning product, apply Python expertise, collaborate with teams, and support customer implementation for success.

Develop ML models to detect fraud, collaborate with teams to deploy solutions, and improve ML processes while mentoring teammates.