Top Machine Learning Engineer Jobs in NYC, NY

Lead ML engineer responsible for designing, building, deploying, and monitoring production ML systems at scale. Collaborate with product and data science teams, develop ML architectures and data pipelines, apply CI/CD and cloud-based MLOps, retrain and govern models, and ensure performance, reliability, and responsible/explainable AI practices.

Lead design, build, and productionize scalable ML models and pipelines. Collaborate with product and data science teams, implement cloud-based architectures, ensure CI/CD, monitoring, model governance, and responsible AI practices.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

The role involves designing and building AI-enabled investment management platforms, developing scalable APIs, and collaborating with engineering teams to create AI solutions.

Design, build, and productionize large-scale foundation models and ML systems (transformer architectures, self-supervised learning). Architect and implement training, data pipelines, deployment, monitoring, and CI/CD. Collaborate with cross-functional teams, ensure model governance, reliability, and performance, and apply ML engineering best practices at scale.

This role involves building and optimizing ML systems and frameworks, collaborating with teams to enhance research and development in ML models.

As an MLOps Engineer II, you'll enhance ML workflows, support engineers, improve model deployment processes, and advocate for best practices across teams.

Design, build, and productionize ML models and infrastructure at scale. Collaborate with product and data science teams, develop and validate models, construct data pipelines, deploy and monitor models, apply CI/CD, and ensure Responsible/Explainable AI and high availability for ML systems.

The Senior Principal Engineer will lead the development of ML systems at SoundCloud, focusing on recommendation and personalization techniques while mentoring engineers and driving strategic direction.

Lead the design and implementation of scalable AI systems focusing on large language models and speech technologies, while providing technical leadership and mentoring.

As a Machine Learning Engineer, you'll build and enhance features for a search stack, design ML/NLP solutions, and implement an experimentation framework while ensuring code quality.

The Machine Learning Engineer will design and build scalable ML data pipelines, manipulate 3D data, collaborate with customers, and ensure reliable deployment of ML systems.

The role involves designing large-scale data pipelines for machine learning, improving ML workflows, and ensuring efficiency in distributed model training environments. Key responsibilities include developing infrastructure, integrating ML pipelines, optimizing performance, and collaborating with ML engineers on large-scale experimentation.

As a Machine Learning Engineer II, you will enhance AI systems for automating customer operations, develop evidence extraction pipelines, and collaborate with teams on model development and deployment.

The Lead Machine Learning Engineer will design, build, and productionize ML applications, oversee model performance, collaborate with teams, and ensure reliable deployment of ML systems at scale.

As a Machine Learning Engineer at Finch, you will build and deploy production ML systems, collaborate with product and legal teams, and improve AI accuracy and reliability.

The Senior AI/ML Engineer will develop and improve analytical tools, approaches, and architecture for scalable AI and machine learning solutions, collaborating with engineers and data scientists on innovative projects.

As a Machine Learning Engineer on the Personalization team, you'll develop and enhance recommendation systems, collaborate across teams on ML projects, and promote best practices in ML systems development.

The Machine Learning Engineer at Lyft will design, build, and deploy ML models across various domains, collaborating with data scientists and product managers to solve complex business problems at scale.

Lead the design, development, and deployment of foundational ML systems, influence architecture, mentor engineers, and drive strategic initiatives within SailPoint's AI team.

Build and scale LLM-based, agentic customer-engagement systems: architect, deploy, and monitor production ML features; finetune models; create evaluation frameworks, feedback loops and HITL workflows; run A/B tests; optimize latency, cost, and reliability; and mentor the team.

Work with enterprise customers to deploy, troubleshoot, and operationalize AI systems. Design integrations across APIs, infrastructure, and governance platforms; deploy evaluation, observability, and guardrail solutions; translate deployment challenges to product and engineering teams; and balance technical and business requirements to drive customer adoption.

The role involves building, optimizing, and scaling AI agents for finance teams, integrating data sources, and improving AI system performance.

The Principal AI/ML Engineer will lead the design, implementation, and deployment of AI systems, mentor junior engineers, and ensure model performance and reliability in production environments.

The Machine Learning Engineer will propose technical initiatives, lead design discussions, translate challenges into plans, and uphold engineering standards.