Top Machine Learning Engineer Jobs in NYC, NY

As a Staff Applied AI Scientist, you will design and deploy AI systems using LLMs, improve agent performance, and collaborate with engineering to enhance systems for customer impact.

The role involves building and maintaining machine learning models for user safety, managing projects, and collaborating with various teams to implement advanced AI techniques.

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

Design and build ML infrastructure, influence data access and model deployment, partner with researchers to optimize ML models for trading, and mentor engineers.

Lead the design, development, and deployment of AI software components while partnering with engineers and scientists to deliver innovative AI solutions at Capital One.

The Director of AI Platform will lead technical vision for Aladdin's AI platform, overseeing AI initiatives, engineering standards, and team development, ensuring responsible deployment of AI solutions.

The role involves designing and deploying AI systems for vaccine discovery, leading predictive modeling, integrating datasets, and mentoring colleagues on AI applications in vaccinology.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

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

Lead the development of production-grade ML systems, aligning technical roadmaps with company priorities, mentoring ML engineers, and ensuring ethical use of ML/AI.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

The Machine Learning Engineer will design, build, and deploy ML applications at scale, collaborating with cross-functional teams and applying best practices in ML engineering and cloud technologies.

As a Machine Learning Engineer in Fraud Risk, you'll build and maintain ML systems for fraud detection and anomaly analysis, ensuring robust performance and real-time decision making.

Lead the design and deployment of machine learning models for personalized navigation and recommendations, managing projects end-to-end with a focus on user-centric solutions.

Design and deploy ML models for fraud detection, develop data pipelines, partner with teams to ensure effective fraud prevention, and enhance detection accuracy.

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

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 Senior Machine Learning Engineer, you will design and build ML models for patient-provider matching, focusing on personalization and ranking. Responsibilities include model development, A/B testing, and collaborating across teams to improve patient experiences.

Develop and maintain machine learning models for user safety, design scalable systems, and collaborate on AI solutions while ensuring fairness. Requires strong programming and domain expertise in ML technologies.