Top Machine Learning Jobs in NYC, NY

Work with product and engineering teams to analyze large datasets, build and deploy machine learning and statistical models, develop data pipelines and mining frameworks, generate predictive insights, and present actionable recommendations. May require nights/weekend availability and independent judgment.

Lead data science projects to advance drug development, implementing models for patient selection and clinical trial optimization, and collaborating with cross-functional teams.

As a Data Science Lead, you'll drive AI/ML initiatives, mentor data scientists, collaborate with stakeholders, and ensure effective model deployment and governance.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.

Lead data-science work for matching features: translate product goals into data problems, design and analyze A/B tests, perform exploratory analysis and data mining, generate strategic insights, and collaborate with AI, product, design, and engineering to develop and iterate production ML models.

Lead the development of large-scale recommendation systems at Snap, overseeing technical leadership, collaboration across teams, and implementation of machine learning strategies to enhance content discovery and personalization.

The Staff Applied Scientist will lead the evaluation strategy for AI agent integrations at Datadog, defining metrics and building datasets for quality improvements in agent performance through applied research and technical leadership.

Lead a team in developing AI and ML models focusing on detection and text intelligence. Collaborate with product managers and support team development for impactful AI features.

Responsible for designing and developing AI solutions for Oncology R&D, collaborating with scientists to translate complex questions into actionable insights, and contributing technical expertise in rapidly prototyping AI applications.

The role involves building AI-enabled solutions, developing data pipelines, and collaborating with teams to enhance Oncology R&D workflows.

Lead the Oncology AI product strategy and roadmap, manage AI engineering teams, and drive stakeholder engagement for impactful AI solutions in R&D.

As a Machine Learning Engineer, you will build and deploy models for Snapchat, applying modern ML techniques to solve problems and lead the full ML lifecycle.

The role involves model validation, monitoring AI model performance, challenging model developers, and translating technical requirements into practical evaluations and controls for AI and ML models.

As a Senior Lead AI Solutions Consultant, you will drive revenue through the adoption of BrazeAI tools, managing technical discussions, running proofs-of-concept, and educating clients on AI concepts.

Lead vision, strategy, and delivery of AI across Pfizer's U.S. commercial organization. Own a prioritized portfolio from concept to production and adoption, build and lead multidisciplinary teams, manage vendors and budgets, ensure shared platforms, standards, governance, and responsible AI, and influence senior leaders to drive enterprise-scale transformation and measurable business value.

As an AI Product Specialist, you will define strategies for market expansion and revenue growth of AI-powered solutions, integrating technical understanding with market leadership.

Join Celonis' 12-month Orbit program to consult with customers, prototype AI and ML/LLM solutions on the Celonis platform using SQL and PQL, run proofs of concept, present value to executives, and collaborate with product, implementation, and partners to realize customer value.

The role involves building machine learning models, data analysis, and partnering with various teams to enhance customer experiences in financial services.

Develop, validate, and implement machine learning models using big-data tools and cloud platforms. Partner with engineers and product managers to translate analytics into production products, analyze large numeric and textual datasets, and communicate findings to drive business decisions for commercial banking portfolio forecasting.

The Director will create and manage an advanced learning agenda for AI and data capabilities, focusing on technical skill development for engineers and data scientists, ensuring alignment with real-world applications and industry needs.

The AI Researcher will conduct advanced research in Generative AI and Machine Learning, develop specialized models for observability and code repair, and collaborate with product teams to integrate findings into Datadog's offerings.

The AI Engineer will focus on building AI experiences, deploying models, and enhancing data workflows, working on greenfield applications. Key responsibilities include feature development, architecture collaboration, and shipping impactful product experiences.

Lead evaluation strategy for Datadog Dashboards' AI-native system: define metrics, build eval datasets and regression harnesses, measure retrieval and tool-selection, reduce cost/latency, and provide technical leadership and cross-team mentorship to ensure production-quality agent behavior at scale.

Lead Gusto's AI/ML strategy, managing teams in Machine Learning Engineering, AI, and Risk Data Science. Ensure systems are reliable and impactful while fostering a culture of technical excellence.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.