Top Machine Learning Jobs in Rochester, NY

As a Senior Staff Machine Learning Engineer, drive AI safety initiatives, design monitoring systems, and collaborate cross-functionally to ensure robust, safe AI usage in community support products.

Lead a team of ML engineers to deliver AI/ML solutions on AWS, focusing on practice strategy, operational excellence, and building partnerships.

Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.

As a Cloud Machine Learning Engineer at Hugging Face, you will build ML solutions leveraging cloud technologies, integrate models, design APIs, and contribute to documentation and community advocacy.

Lead the design and execution of ML-based targeting products, improving advertiser outcomes while mentoring junior engineers and collaborating with cross-functional partners.

Lead the design and architecture of GNN and transformer-based multi-entity embedding generation for Reddit's recommendation systems, collaborating across teams and optimizing machine learning pipelines.

The Senior Product Manager will develop AI tools, collaborating with research, engineering, and design to meet user needs and drive business value.

Drive AI/ML-powered personalized experiences on Pinterest by defining product vision, collaborating across teams, and launching new features to enhance user engagement.

The role leads predictive modeling and machine learning initiatives, mentors team members, and drives innovations in data science for credit risk and operations.

As a Machine Learning Engineer, you will design, develop, and deploy machine learning systems, collaborate on AI features, and ensure reliable production performance.

The Principal Machine Learning Engineer will improve diffusion models, conduct research, implement techniques, and collaborate on production-ready systems in AI for fashion.

The Data Scientist will develop machine learning models to optimize software build processes, analyzing large datasets and collaborating with teams for improvements.

The Staff ML Ops Engineer builds and maintains infrastructure for ML applications, ensuring they are robust and production-ready, while collaborating with data scientists and ML engineers.

The Staff Software Engineer, AI/ML will design and develop intelligent agents, integrate them with existing systems, optimize performance, and collaborate with product teams, focusing on innovative AI technologies.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

The Senior Applied Scientist will develop and integrate advanced AI/ML models for estate planning, leading projects and collaborating with teams on complex data processes and applications.

Design and implement ML systems for ads targeting, drive technical direction, mentor junior engineers, and collaborate cross-functionally for product development.

The role involves leading ML/AI solutions, managing technical roadmaps, collaborating with stakeholders, and driving innovation in products and services.

Build and implement AI solutions for cybersecurity, focusing on vulnerability detection and exploitation. Collaborate with senior engineers and mentor junior team members.

The Machine Learning Engineer will build and scale ML models, collaborate with cross-functional teams, and improve real-time recommendations for Stitch Fix's clients.

Design and architect AI/ML solutions, build document parsers and classifiers, maintain AI systems, and collaborate with cross-functional teams.

The Software Engineer will develop machine learning infrastructure, optimize models, and create tools for data analysis while collaborating with a diverse team.

The role involves sourcing and recruiting senior engineers in AI, ML, and related fields, building talent pipelines, and collaborating with engineering leadership.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

Lead the design and implementation of deep learning models for biological data, focusing on model architecture, project leadership, and innovation in machine learning applications in biology.