Top Remote Machine Learning Jobs in Rochester, NY

The Machine Learning Engineer will design and implement AI/ML projects on AWS, optimize data architectures, and ensure secure data management.

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

The role involves deploying, optimizing, and maintaining ML-driven motion planning and control algorithms for autonomous driving, collaborating across teams to ensure reliability under performance and safety constraints.

The Senior Machine Learning Engineer at Grailed will enhance personalization and recommendations, develop AI/ML solutions, and collaborate across departments for data-driven insights.

As a Software Engineer in ML Infrastructure, you will develop scalable data pipelines, enhance data discovery, and collaborate with teams on data organization and ML features.

The Director of Machine Learning Science will lead teams in delivering ML solutions, drive innovation in search and personalization, and engage with engineering and product teams.

The Machine Learning Engineer will design and deploy computer vision models, build training pipelines, and enhance ML infrastructure to improve agricultural field operations.

Intern will collaborate with data scientists and ML engineers to develop machine learning models and improve data pipelines for retail media insights.

Senior ML research leader who translates state-of-the-art ML pipeline insights into product requirements, reference architectures, benchmarks, and platform roadmaps. Partners cross-functionally and with strategic customers and research institutions to set evaluation standards, reproducibility, and responsible ML practices while providing technical leadership and influencing product and executive audiences.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

Design, architect, and deploy generative AI/LLM solutions from prototype to production; work directly with clients to translate business needs into technical plans; write production-quality code integrating LLMs and ML models; collaborate with cloud, DevOps, and frontend teams; support proposals, sales, and evaluation/observability of models.

The Technical Product Manager will define roadmaps for an AI Platform, manage ML systems, partner with engineers, and improve healthcare outcomes.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

Design, build, and maintain forecasting and portfolio optimization models for U.S. power markets; analyze market outcomes, track supply/demand/congestion dynamics, and apply statistical, optimization, and ML methods to inform commercial decisions.

The Director of AI will lead AI and machine learning initiatives, develop AI architecture for humanoid robots, oversee production-ready AI systems, and manage team growth and budget.

The Product Operations Associate will support the development of AI-driven products by ensuring accuracy, documentation, and effective workflows, while collaborating with various teams.

Lead the development of AI-powered tools and products, manage product roadmaps, collaborate cross-functionally, and drive innovation in media and advertising.

Lead content programming through analysis, classification, and editorial judgment. Monitor performance, synthesize query analysis, propose product improvements, curate content, and collaborate with Engineering/Data Science on LLM/ML/NLP initiatives.

Lead Yahoo's Data Activation product area: define vision and strategy, partner with Data Science and Engineering, drive cross-vertical data activation initiatives, deliver measurable business impact, and mentor/manage product teams to execute on audience, personalization, and targeting use cases.

The Senior Data Scientist will design, develop, and own machine learning systems for document verification focusing on computer vision and deep learning. Responsibilities include technical leadership, engaging with customers, and collaborating with engineering and product teams.

The Machine Learning Associate will curate and validate data, generate synthetic datasets, optimize algorithms, and analyze accuracy for machine learning models in retail contexts.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

The role involves designing and supporting GPU/Kubernetes clusters for AI/ML workloads, developing automation tools, and troubleshooting infrastructure issues.

As a Senior Technical Recruiter for AI/ML, you'll manage full-cycle recruiting for senior AI roles, build talent pipelines, and partner with leadership to close top talent effectively.