Top Machine Learning Jobs in NYC, NY

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

The Machine Learning Engineer will build and deploy data products, collaborate cross-functionally, improve customer experiences, and mentor others in AI methods.

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

Lead the technical vision for Upstart's ML and simulations platform, modernizing infrastructure and mentoring a team while collaborating cross-functionally.

As a Sr. Machine Learning Engineer, you will develop and implement models to enhance customer products, manage ML Ops, and oversee data analysis.

As a Machine Learning Engineer, you will analyze complex datasets, develop models, manage ML Ops, and enhance customer products using machine learning techniques.

Manage and lead a team of Analysts, focusing on marketing measurement, optimizations, and utilizing machine learning to enhance campaign performance for clients.

The Senior Machine Learning Engineer will evaluate and apply advanced ML models, integrate with company infrastructure, and support data pipeline orchestration while focusing on autonomous vehicle technology.

The role involves building machine learning models to detect and reduce fraud in Block's Cash App and Square ecosystems. Responsibilities include collaboration with cross-functional teams, developing ML-driven solutions, and improving the ML lifecycle efficiency, while also mentoring teammates.

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 Principal AI/ML Engineer will lead the design and implementation of machine learning solutions in AdTech, focusing on campaign optimization and user personalization while also mentoring other engineers.

The role involves designing and deploying machine learning models, optimizing large language models, and collaborating with cross-functional teams to enhance data management for alternative investments.

Lead the development of ranking and relevance models, design ML systems for patient-provider matching, and mentor junior team members.

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 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.

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.