Top Remote Machine Learning Jobs in Hartford, CT

The Senior ML Backend Engineer will design and maintain backend services, integrate ML models, and ensure compliance and performance within healthcare workflows, while leading technical initiatives and mentoring team members.

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

Seeking a build engineer with strong software engineering skills to manage CI/CD systems and establish best practices for large-scale monorepos for ML applications.

Build a next-generation ML data and feature infrastructure platform to enhance the productivity of ML practitioners and improve feature accessibility.

Lead the design and deployment of machine learning models for personalized healthcare, mentor engineers, and collaborate across teams to improve ML infrastructure.

Lead the architecture and development of machine learning systems for personalized care, treatment intelligence, and automation at scale. Collaborate with cross-functional teams and mentor engineers.

Join Netflix's Algorithms team as a Machine Learning Software Engineer to design and develop solutions for personalization systems. Collaborate on scalable machine learning algorithms and enhance software engineering practices.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

The Principal Machine Learning Engineer will architect and scale ML systems for personalized healthcare. Responsibilities include system design, optimization, technical leadership, and mentoring within the team.

Develop and deploy machine learning models for real-time ad systems, optimizing inventory management, targeting, and campaign effectiveness for Netflix's advertising platform.

As a Sr. Machine Learning Engineer, you will develop and deploy ML models, enhance care personalization, and mentor teams while optimizing workflows.

Responsible for building scalable microservices and data pipelines, mentoring junior engineers, and ensuring data quality for ML training.

Lead a team of ML engineers and software engineers focused on Ads Content Understanding, driving innovation and efficiency in Ads Monetization.

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

Lead the architecture and development of AI and ML features, design evaluation frameworks, and mentor team members to enhance ML-driven product experiences.

Drive cross-team engineering efforts to improve user experience on Homefeed by implementing large-scale machine learning systems and enhancing data processing efficiency.

Design and optimize ML models for AI-powered facial analysis, focusing on computer vision and generative models, ensuring accuracy and efficiency in a B2B SaaS environment.

Seeking a senior product designer for AI/ML platform development, responsible for transforming user experiences, leading projects, and mentoring designers. Emphasis on design impact and collaboration with cross-functional teams.

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

As a Senior Applied Machine Learning Engineer at Upwork, you'll leverage advanced machine learning techniques to enhance search and recommendation systems, analyze data to improve user experience, and develop large language models.

The Senior Machine Learning Engineer will lead ML initiatives, design scalable systems for data processing, and mentor colleagues to build robust ML infrastructure.

The Senior Machine Learning Engineer will design and implement ML solutions, collaborate with teams, and contribute to scalable infrastructure enhancements.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead the technical vision and architecture for machine learning and data systems, overseeing scalable infrastructure and collaboration across teams.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.