Top Remote Machine Learning Engineer Jobs in NYC

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

Develop and deploy machine learning models for risk assessment, collaborating with teams to enhance Gusto's product offerings while ensuring model performance and reliability.

Design and develop scalable AI/ML solutions while mentoring teams and collaborating with cross-functional partners to enhance customer experience through data-driven insights.

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 development of AI/ML solutions for healthcare using structured and unstructured data. Build and test deep learning and classical ML models, design experiments, perform statistical analysis and visualizations, ensure responsible AI compliance, produce documentation/patents/publications, and collaborate on MLOps pipelines and stakeholder integrations.

Build and own full-stack UX and backend systems for the ML lifecycle: design architecture, integrations, observability, CI/CD, and production frontend/backends. Lead technical initiatives, mentor engineers, and collaborate across teams to scale ML platform capabilities.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising 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 will build and deploy ML models, applying modern techniques to solve problems and collaborate with teams on ML-driven features.

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

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 Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The role involves building computer vision models, researching deep learning methods, handling large datasets, and implementing MLOps best practices.

Design and build ML features using LLMs, collaborate on technical architecture, and ensure safety and performance of deployments.

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

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

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.

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.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

As an ML Engineer, you'll build and deploy scalable ML systems, optimize models, and collaborate with teams to improve content across platforms.

As an ML Engineer Intern, you will build and deploy ML models, design scalable infrastructure, and collaborate with data science teams in a fast-paced environment.

Lead the design, implementation, and scaling of ML infrastructure and production AI systems. Optimize workflows, collaborate with teams, and mentor engineers.

Lead the development of Computer Vision and Machine Learning projects at Dandy, focusing on 3D geometric problems and automation in dental manufacturing.