Top Senior Machine Learning Jobs in Hartford, CT

The role leads the design and delivery of AI-powered technology to enhance productivity in claims operations, managing cross-functional teams to achieve strategic objectives.

Lead go-to-market strategy, positioning, and messaging for Elsevier's Academic Leaders and Funders portfolio. Translate technical AI and data capabilities into compelling narratives, drive coordinated product launches, enable sales with materials and training, and perform competitive and market analysis to increase adoption, deal velocity, and revenue.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

The Senior Product Manager will define product strategy, manage SaaS product enhancements, drive innovation in data governance, and collaborate across teams to deliver customer-centric solutions.

Build and maintain backend services and scalable, parallelized data pipelines for Recruiting AI. Productionize microservices exposing classifiers/ML models, design message-based APIs, ensure enterprise SLAs, CI and test suites, and collaborate with data scientists, DevOps, product and engineering teams to integrate services into production.

Develop and maintain backend services for SmartPal conversational AI: design and implement Python services on Kubernetes/AWS, connect to MongoDB/PostgreSQL, build RESTful APIs, implement test automation, and collaborate across discovery, prototyping, and production monitoring.

Join the SmartPal backend team to design and build Python services on Kubernetes/AWS, connect to MongoDB/PostgreSQL, create developer-friendly RESTful APIs, automate tests, and contribute product ideas for a conversational AI platform.

Lead architecture, design, development, deployment, and optimization of an agentic AI platform. Partner with product, data, security, and business teams to productionize AI solutions, establish engineering best practices, mentor teams, and drive reusable AI services, automation, and operational improvements to deliver business impact.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

Lead product initiatives from discovery through launch for healthcare SaaS products using analytics and ML. Own roadmap, prioritize backlog, partner with engineering/design/data, use qualitative and quantitative evidence, and drive adoption and measurable customer impact.

Own Cash Application and Deduction Resolution Management products end-to-end. Lead discovery, define requirements, prioritize roadmap, partner with engineering/design/sales, ensure financial accuracy, build ERP integrations, drive launches, and maintain product quality and customer-focused outcomes.

The Enterprise Architect leads architectural strategy and integration for technology and processes while aligning IT investments with business goals. Responsibilities include overseeing cloud modernization, governance, and communication with stakeholders.

The Director of Product Management will oversee the product lifecycle for AI products, focusing on customer collaboration, rapid prototyping, and product strategy. The role involves leading product teams, driving execution, and shaping the product culture.

The SAP Innovation Architect will design SAP automations, mentor engineers, and drive innovation in AI-driven SAP operations, while ensuring scalability and security in integrations.

As a Principal Machine Learning Engineer, you will develop multimodal AI experiences, design agent interactions, and lead cross-team initiatives while ensuring AI safety and reliability.

The VP will transform R&D operations by embedding AI into product workflows, enhancing efficiency and decision-making across teams. They will lead system redesign, implement AI-driven analytics, and establish KPIs for continuous improvement.

The Senior Data Scientist will develop scalable ML models, analyze large datasets for insights, and collaborate with teams to enhance business performance through data-driven solutions.

As a Staff Software Engineer, you'll lead the development of AI-driven automations, improving data integration and platform capabilities for cybersecurity teams with over 8 years of experience in complex backend applications and distributed systems.

Lead vision, strategy, and roadmap for pricing platforms, owning internal Rating Plan Manager and tooling to speed model deployment, improve workflow reliability and observability, enable self-service experimentation, and support regulatory/state-level pricing needs through cross-functional collaboration.

Design, develop, and deploy causal inference and predictive models (uplift, synthetic control, DML) for customer loyalty, churn, and LTV. Build foundational data models and scalable features, perform large-scale SQL ETL, operationalize models in cloud, partner with stakeholders, and present insights to drive revenue and loyalty program optimization.

Lead architecture and development of a SaaS platform for data center energy procurement. Build forecasting, contracting, and monitoring modules; implement AI tools on AWS (Bedrock, SageMaker); hire and mentor engineers; translate business logic into scalable systems; deliver demos to investors and customers.

Lead end-to-end product for an enterprise AI security product: set roadmap, build product processes, run customer discovery with security practitioners, partner with engineering to ship ML/AI features, and enable GTM. Build the product function from scratch and define metrics, specs, and AI quality measures to drive adoption, retention, and expansion.