Top Machine Learning Jobs in Rochester, NY

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

As a Systems Architect, you'll define and drive the infrastructure architecture for AI/ML workloads, design multi-cloud strategies, manage compute orchestration and storage systems, and lead capacity planning, while also collaborating with engineering leadership.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

As a Forward Deployed Machine Learning Engineer, you'll build and deploy machine learning models, enhance system performance, and collaborate with Data Science and Engineering teams for effective solutions.

Support Midstream and Growth programs by developing and maintaining BI dashboards, translating business requirements into KPIs and data models, leading data validation and governance, providing ad-hoc analytics and scenario modeling, driving BI capability development, and partnering on strategic digital transformation and reporting roadmap initiatives.

Lead CX transformation engagements by driving client discovery, maturity assessments, journey analysis, and presales solutioning. Design Conversational AI/CCaaS-based solutions, craft proposals and demos, collaborate with sales and delivery, and influence C-level stakeholders to deliver measurable CX improvements and ROI.

This is a general talent-community application inviting candidates across many functions to submit resumes. Recruiting will review and retain applications for future openings; candidates should highlight experience, accomplishments, and interests for potential remote roles.

Conduct ML research for query understanding, ranking, clustering, and AI-powered search. Prototype and productionize algorithms, define data and evaluation requirements, design scalable systems, collaborate with engineers, run experiments, and publish patents/papers to integrate state-of-the-art ML into Yahoo Search products.

Own OEM-facing product roadmap for the Automotive Enterprise Cloud, translate OEM requirements into scalable integrations (APIs, data pipelines, reporting), lead discovery and delivery with cross-functional teams, define success metrics, produce product artifacts, and drive OEM adoption and satisfaction.

This role involves leading strategic planning, product innovation, and cross-functional collaboration to enhance pharmacy analytics and drive growth initiatives for CVS Health.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

The Senior Director of Data Science & AI leads AI strategy execution, managing a multidisciplinary team to develop and govern AI solutions, with a focus on innovation, operations, and ethical standards.

Lead the Client Solutions team, ensuring the execution of complex transactions while driving innovation and client advocacy. Oversee operations, build client relationships, and implement strategic frameworks for growth.

Contract Technical Recruiter (12-month, hybrid in Austin) partnering with engineering leaders to source, attract, and hire AI/ML, systems software, and hardware engineering talent. Build hiring strategies, talent pipelines, and targeted sourcing campaigns, deliver a high-touch candidate experience, and share market intelligence to improve recruiting outcomes.

The AI & Data Science Director will lead AI strategies, foster technical leadership, support team development, and integrate generative AI into products.

Lead development of an AI-enabled Ethereum Layer 2 platform: build front-end and back-end systems, deploy and optimize AI models, create data pipelines, collaborate on model training, and contribute to product innovation and other company projects.

Design, build, and modernize telecom OSS/BSS and 5G core components using cloud-native microservices, Kubernetes, and real-time streaming. Implement API-first integrations (TM Forum Open APIs), CI/CD, Helm/Istio, and production ML for predictive maintenance and fraud detection. Manage legacy migrations, multi-vendor integrations, edge/MEC and network-slicing orchestration, and enforce zero-trust security and SBOM practices to ensure resilient, scalable network operations.

Serve as primary post-sales relationship owner for federal customers, driving onboarding, adoption, and retention of HiddenLayer cybersecurity/AI solutions. Coordinate cross-functional teams, conduct business reviews, mitigate risks, capture customer feedback, and support renewals and expansion in complex federal environments.

Sell HiddenLayer's AI security platform to federal agencies by developing account strategies, driving pipeline and revenue, leading technical and executive engagements, navigating federal acquisition and contracting, coordinating cross-functional teams, and supporting adoption, expansion, and renewals across the Intelligence Community, DoD, DHS, and civilian agencies.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

As Software Engineering Manager, you'll lead a team in enhancing content workflows through automation and AI, develop scalable solutions, and manage cross-functional collaboration.

Develop and deploy end-to-end machine learning solutions, collaborate with cross-functional teams, and implement MLOps frameworks while monitoring model performance in production.

The Data Science Actuary role involves building and maintaining rating systems and risk models, conducting analysis for underwriting and operations, and integrating new data sources while collaborating with multiple teams.

The Senior Generative AI Engineer will design and deploy AI/ML solutions, focusing on Generative AI systems and their operational excellence across various sectors like R&D and Clinical Trials.