Top Machine Learning Jobs in NYC, NY

Develop and deploy machine learning applications, collaborating with teams to solve business challenges. Create ML solutions, analyze data, and communicate results.

Design, build, and deliver machine learning models and components. Ensure performance and monitor models in production as part of an Agile team.

The role involves designing, developing, and supporting AI and ML products, collaborating with teams to transform risk management and deliver value to customers through technology.

The Machine Learning Engineer will develop intelligent features to enhance code security using LLMs, collaborate with researchers, and manage ML models on AWS.

The role involves designing and deploying ML models for domain search, including ranking and personalization, while collaborating with cross-functional teams.

Lead development and deployment of advanced ML models for heart disease diagnostics, providing technical leadership and guiding projects through regulatory approval and clinical integration.

The Staff Machine Learning Engineer will define technical strategies, design ML models for document processing and risk assessment, and build scalable ML systems to protect Coinbase users' funds.

The Staff Machine Learning Engineer will utilize AI models, mentor team members, and enhance automation solutions across Coinbase's operations, focusing on machine learning to solve complex challenges.

The Senior Machine Learning Engineer will develop models and algorithms for NVIDIA's DGX Cloud, focusing on anomaly detection, optimization, and forecasting. Responsibilities include analyzing data, collaborating with teams, and delivering impactful machine learning solutions.

Develop and deploy machine learning models for risk assessment, collaborating with teams to enhance Gusto's product offerings while ensuring model performance and reliability.

As a Senior Machine Learning Engineer, you will design, build, and deploy large-scale ML systems to enhance Dropbox's AI features, collaborating with teams and mentoring peers.

Machine Learning Engineers at Tennr will architect, train, deploy models, optimize data pipelines, integrate ML into backend systems, and collaborate with teams for product evaluation.

The Applied Scientist will design and implement machine learning models, collaborate across teams, improve model performance, and contribute to internal research initiatives.

Lead the development of machine learning models for advertising products, optimizing strategies and driving business-critical outcomes.

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

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 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.