Top Machine Learning Jobs in Providence, RI

Lead QA for AI/ML features: design and execute test plans, build Python automation to validate LLM outputs, guardrails, and data pipelines; perform regression, security/privacy validation, and analyze logs/metrics to ensure reliability.

Design and build machine learning models for Zillow's product features, optimize AI components, and mentor engineers within a cross-functional team.

Lead data acquisition and management strategies for AI models, analyze data systems, oversee partnerships, and guide a team in optimized data usage.

Lead the definition and rollout of AI-powered product features, collaborating with teams to enhance fraud prevention solutions.

Manage a team of data scientists and analytics engineers to innovate Netflix's core product experience, driving measurement and insights across the TV and interactive discovery domains.

Lead the development of first-party measurement solutions, integrate with third-party partners, and ensure high-quality analytics outputs within the ads ecosystem.

Lead Reliability & Observability initiatives, collaborate with engineering and product teams, ensure robust operations of Airbnb's platform, and drive AI projects.

Design, build, and scale data and ML systems; collaborate cross-functionally; implement data quality and governance frameworks; document data processes.

The Senior Machine Learning Engineer will build and operate ML systems end-to-end, focusing on production-grade ML platforms, feature pipelines, and MLOps practices while collaborating with cross-functional teams.

The Machine Learning Engineer will develop and integrate ML solutions, maintain ML systems, build data pipelines, and collaborate with cross-functional teams.

Analyze biological datasets using machine learning and deep learning, collaborate on research projects, and communicate findings through visualizations and reports.

The AI/ML Specialist Solution Architect Intern will assist in designing AI solutions, learning about distributed workloads, and preparing technical materials, gaining mentorship and exposure to modern ML frameworks and GPU infrastructure.

The Staff ML/AI Platform Engineer will design, prototype and deploy AI/ML models, optimize pipelines, mentor junior engineers, and collaborate closely with other teams to develop machine learning solutions.

Design and implement production-grade ML systems for ICS/OT cybersecurity, build and optimize models (including NLP/LLMs), develop data pipelines and MLOps workflows, collaborate with data teams to deploy and monitor models in cloud and on-prem containerized environments, and troubleshoot production performance and resource issues.

The Senior Product Manager will lead the development of medication prescribing capabilities, utilizing AI and machine learning to enhance member experiences and drive health engagement.

Lead multi-year strategy, roadmap, and execution of Upwork's reputation systems. Own cross-functional delivery of reputation, trust, and ranking initiatives, define success metrics linking reputation to marketplace outcomes, and build and mentor a team of product managers to drive adoption and measurable business impact.

As an AI Applications Engineer, you will bridge AI research and implementation, driving experiments, building infrastructure, and releasing products to improve user experience and metrics.

Lead the design, execution, and analysis of machine learning-driven product experiments to optimize ordering systems. Collaborate with stakeholders and mentor teams.

The Director of Artificial Intelligence will define, lead, and implement AI strategies, managing R&D, building teams, and ensuring ethical AI use to drive business outcomes.

The VP of AI will lead NeoWork's AI strategy, ensuring adoption, developing workflows, building capabilities, and enhancing client value through AI integration.

Lead the implementation of AI-driven supply chain solutions, collaborating with clients to enhance their business processes and ensure seamless technology integration.

Manage and mentor engineers, contribute to product and infrastructure, drive projects, and collaborate cross-functionally to enhance AI platforms.

The role involves defining the vision and strategy of the Outreach AI Platform, prioritizing the roadmap, collaborating with engineering and data science teams, and engaging with customers to refine AI strategies.

Lead ML strategy and standards as a senior individual contributor: define ML infrastructure, tooling, and lifecycle processes; establish monitoring and feature patterns; partner across platform, data, and product teams; mentor data scientists and ML engineers to scale reliable production ML systems.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.