Top Machine Learning Jobs in Providence, RI

The Software Engineering Manager will lead a team in creating tools for Cengage Learning Platforms, focusing on AI innovation, team growth, agile delivery, and collaboration.

The Director of Research Innovation & Enablement will lead AI integration into research, manage researchers, and enhance workflows for insight generation and efficiency.

The Business Development Manager leads strategies for growth in telecom accounts, engaging stakeholders to develop AI/ML-driven solutions, and managing partnerships in a fast-paced environment.

The Sr. Solution Engineer collaborates with Sales to advance enterprise opportunities, conducting demos, workshops, and assessments to align with customer needs and position Aera's Decision Intelligence platform as a transformative solution.

The Senior Technical Recruiter will manage the full-cycle recruiting for technical roles in Data, Machine Learning, and Software Engineering, working closely with engineering leadership to build talent pipelines and evaluate candidates' technical skills.

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

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

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

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.

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.

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.

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.

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

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

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

Develop and deploy production-grade AI/ML models, design end-to-end pipelines, and ensure compliance while collaborating with stakeholders in a federal environment.

As an Associate Technical Architect in Machine Learning, you will design and develop advanced ML models on AWS, ensuring scalability and reliability while collaborating with cross-functional teams.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

The AI/ML Engineering Manager leads a team of ML engineers and architects, managing hiring, performance, and customer engagements while providing technical guidance in ML operations and architecture.

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

The ML Administrator will manage machine learning model governance, optimize ML infrastructure, and validate AI/ML pipelines to support DoD projects.

The Machine Learning Engineer II will enhance ML capabilities for autonomous vehicles, train and optimize models, and ensure high performance through collaboration with cross-functional teams.

The Senior Product Manager will develop AI-driven capabilities for SurveyMonkey's platform, collaborating with engineering and data science teams to enhance user interaction and feedback collection.