Top Remote Machine Learning Jobs in Rochester, NY

The Machine Learning Engineer will execute the full ML lifecycle, collaborating on model implementation and improving customer experiences through data-driven insights.

The AI Strategist leads AI initiative ideation and planning, collaborates across departments to define use cases, and ensures alignment with strategic and regulatory goals.

The role involves leading ML client engagements, shaping strategies, advising on ML architecture, and influencing project outcomes, while guiding teams and driving business value.

The Machine Learning Engineer will develop AI/ML projects on AWS, optimize data systems, support cloud migration, and handle various data types and structures.

As a Senior Machine Learning Engineer, you will develop and deploy ML models for health data analysis, collaborating with cross-functional teams to ensure reliability and regulatory compliance.

Build a next-generation ML data and feature infrastructure platform to enhance the productivity of ML practitioners and improve feature accessibility.

Join Netflix's Algorithms team as a Machine Learning Software Engineer to design and develop solutions for personalization systems. Collaborate on scalable machine learning algorithms and enhance software engineering practices.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

As a Full Stack Engineer, you'll develop production-ready AI and ML features, build APIs, design scalable systems, and implement frontend solutions using Angular.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

As a Senior Machine Learning Scientist, you will design, build, and optimize deep learning models for biological data analysis, ensuring high-quality outputs and leading complex projects from conception through deployment.

The Senior Machine Learning Engineer will manage the full ML lifecycle, collaborating with teams to develop scalable systems that improve product decisions and empower monetization strategies.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

Lead the development of a robotics data platform, focusing on data enablement, API architecture, and mentoring engineers in complex system designs.

As a Data Scientist, you will deliver data insights using AI, ML, and analytics, build scalable models, and collaborate on data engineering projects while mentoring junior team members.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

Develop and optimize unimodal and multimodal perception models for 3D/BEV terrain and surface inference, build large-scale data pipelines and annotation tools, deploy and optimize models on edge compute, collaborate with robotics/software/hardware teams, mentor juniors, and translate research into production-grade autonomous vehicle perception systems.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

The Senior Machine Learning Engineer will develop AI products, support feature implementation, and troubleshoot ML services to enhance customer experiences.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.

The VP of Research, Machine Learning will set research direction for AI systems, focusing on context representation, reasoning, and evaluation frameworks while ensuring product safety and alignment.

Responsible for building and maintaining end-to-end ML pipelines and deploying production-grade ML systems. Tasks include model fine-tuning, evaluation, and collaboration with engineering teams.

As an AI/ML Data Engineer, you will design and build data and ML infrastructure to create personalized student experiences, working on ETL processes, feature stores, and collaborating with product and data science teams.