Top Machine Learning Jobs in NYC, NY

As a PhD Intern, you will design, develop, and implement software solutions for automated trading systems, collaborating with quantitative researchers.

The role involves designing and deploying machine learning systems for a search platform, focusing on ranking and retrieval while collaborating with cross-functional teams.

Analyze malware and detection tickets to improve detection capabilities. Collaborate with internal teams on threat detection inquiries and perform tasks to manage false positives.

As a Staff Machine Learning Engineer, you will set the technical direction for the Ad Ranking team, design and deploy machine learning solutions, and mentor engineers while driving large cross-team initiatives.

As a Staff Machine Learning Engineer, you'll lead the Content Ranking team in enhancing machine learning models for video recommendations, ensuring scalability, performance, and technical direction across teams.

Lead AI/ML initiatives, manage teams, develop strategies, oversee projects, provide mentorship, and ensure technical excellence in machine learning integrations.

The role focuses on developing data-driven models for optimizing catalyst materials via machine learning and quantum mechanical simulations, collaborating on catalysis research.

The role involves designing and implementing AI/ML-driven capacity forecasting models, collaborating with cross-functional teams, and optimizing resource demand across infrastructure environments.

As a Senior Engineering Manager for ML & AI, you'll lead Data Science and ML initiatives, mentoring team members, and collaborating across R&D to drive strategic AI solutions that impact the business.

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.

Join Freed as an ML Engineer to optimize speech recognition models and infrastructure. Contribute to AI solutions improving clinician satisfaction.

Lead centralized Machine Learning efforts at Affirm, managing model development lifecycles, fostering AI adoption, and overseeing a team of ML professionals to enhance business outcomes.

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

As a Machine Learning Engineer, you'll build and deploy models for core products, apply ML techniques to solve problems, and collaborate on features.

Lead a machine learning engineering team to develop ranking models. Manage project design, code reviews, collaborate with stakeholders, and ensure product scalability and quality.

As a Senior Machine Learning Engineer, you'll design and implement ML applications, collaborate with teams, and ensure high performance and governance of models.

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

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

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

As a Summer Intern on the Collection Platforms & AI team, you will develop ML products, analyze data, and support software design and development, enhancing existing solutions.

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.

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

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

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