Top Machine Learning Jobs in Hartford, CT

The AI Forward Deployed Engineer designs and implements AI solutions, collaborating with stakeholders, enhancing reliability, and producing reusable resources. Responsibilities include diagnosing AI solution issues and engaging with finance and data teams.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

The Staff Advanced Analyst will drive data analytics to improve CS Safety experiences, influence product decisions, and build measurement tools using data-driven insights.

Lead the Marketplace engineering team to enhance the renter experience by developing scalable systems, managing teams, and collaborating with cross-functional stakeholders to drive product strategy.

As Engineering Manager for the Marketplace team, lead full-stack engineers, drive strategic vision, manage team processes, and enhance user experience using AI and ML innovations.

The Customer Success Manager will manage post-sales relationships, drive customer engagement and ROI, and advocate for client needs within the Buzz Solutions platform.

The role involves leading a team to manage data strategies and analytics for Netflix Games, requiring expertise in data science, business analytics, and team management.

As a Solutions Engineer, you will drive sales growth, support partnerships, and deliver AI-driven solutions while collaborating with various teams.

The Product Manager will lead the development of data-driven product capabilities at Axuall, ensuring features are delivered on time and meet customer needs through collaboration with various teams.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

Design, build, and deploy scalable ML and AI systems for Airbnb Customer Support. Lead LLM-based solutions (fine-tuning, RAG, evaluation), collaborate cross-functionally, and drive early-stage ML initiatives to production.

Lead design, development, and productionization of advanced ML models and data pipelines. Drive architecture, experimentation, validation, and best practices while mentoring ML engineers and delivering scalable, business-driving AI solutions.

The role involves building bioinformatics and ML pipelines, analyzing multi-omics data, mentoring, and collaborating across teams to develop actionable insights and scientific breakthroughs.

Design and deliver customer experience solutions using machine learning techniques, analyze customer data, implement ML algorithms, and automate processes.

Work with the product team on automating data ETL pipelines, deploying ML models, and connecting ML models to user interfaces. Collaborate with cross-functional teams on product development.

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

Design, develop, and deploy machine learning models; analyze large datasets; build scalable data pipelines and distributed computing environments; integrate ML solutions with cross-functional teams; optimize performance and support production ML infrastructure.

Lead and grow a global data engineering and ML organization, design cloud-native data platforms and pipelines, deliver ML-powered products, establish engineering and MLOps best practices, and support sales through solutioning and client-facing technical leadership.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.

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.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

As a Senior Machine Learning Engineer, you'll develop models for risk identification, collaborate cross-functionally, and deploy ML solutions, ensuring performance monitoring and continuous improvement.

Lead the vision, strategy, and execution of the machine learning platform at Flex, focusing on compliance, customer success, and internal operations. Build and mentor a team of ML engineers and data scientists to deliver scalable ML systems.

The Business Analyst 2 analyzes AI-powered data solutions, optimizes customer experience automation, and collaborates with teams to drive business insights and value.

The Research Scientist will conduct studies on natural language processing and machine learning, transition models to production, conduct experiments, publish research, and create new models to enhance products.