Top Machine Learning Jobs in Hartford, CT

Design, build, and maintain forecasting and portfolio optimization models for U.S. power markets; analyze market outcomes, track supply/demand/congestion dynamics, and apply statistical, optimization, and ML methods to inform commercial decisions.

The Director of AI will lead AI and machine learning initiatives, develop AI architecture for humanoid robots, oversee production-ready AI systems, and manage team growth and budget.

The Product Operations Associate will support the development of AI-driven products by ensuring accuracy, documentation, and effective workflows, while collaborating with various teams.

Own U.S. client relationships: act as main contact for strategic accounts, manage renewals and contracts, identify upsell/cross-sell opportunities, monitor client health, maintain CRM records, gather client feedback, and help grow long-term partnerships.

Lead the development of AI-powered tools and products, manage product roadmaps, collaborate cross-functionally, and drive innovation in media and advertising.

Partner with Account Executives to deliver technical demos, PoCs, and proposals; design integrations and architectures; support evaluations, onboarding, and cross-functional handoffs; train teams and build technical assets.

Lead the Intelligent Document Processing product to improve extraction and classification accuracy. Define the IDP roadmap, partner with Data Science and Engineering to raise F1/precision/recall, manage ML model lifecycles at scale, benchmark competitors, optimize human-in-the-loop workflows, and ensure extracted data integrity across enterprise systems.

Lead content programming through analysis, classification, and editorial judgment. Monitor performance, synthesize query analysis, propose product improvements, curate content, and collaborate with Engineering/Data Science on LLM/ML/NLP initiatives.

Lead Yahoo's Data Activation product area: define vision and strategy, partner with Data Science and Engineering, drive cross-vertical data activation initiatives, deliver measurable business impact, and mentor/manage product teams to execute on audience, personalization, and targeting use cases.

The Senior Data Scientist will design, develop, and own machine learning systems for document verification focusing on computer vision and deep learning. Responsibilities include technical leadership, engaging with customers, and collaborating with engineering and product teams.

The Staff Threat Researcher and Intelligence Engineer leads advanced research on cyber threats, architects scalable intelligence workflows, and mentors team members while collaborating with various stakeholders.

Lead the Data Engineering team, developing data solutions that enhance AI and ML capabilities, while establishing data engineering standards and mentoring engineers.

Lead multi-team technical strategy and architecture for large-scale, long-lived systems. Design for scalability, reliability, and maintainability; integrate and productionize ML/NLP and anomaly detection; define testing and validation frameworks; align cross-functional teams and mentor engineers to deliver high-quality, business-driving solutions.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Lead a team optimizing backend systems for Netflix's Member Experience Pages. Focus on performance, scalability, architecture, and team growth while collaborating with various stakeholders.

The Data Scientist will analyze and model data related to ad-tier members, focusing on identity modeling and improving ad targeting capabilities, while collaborating with cross-functional teams.

The Manager, Growth Analytics & Marketing Science will build and evolve marketing measurement frameworks, drive analytics, and optimize marketing strategies through data and AI.

The Core Engineer will develop backend systems, utilize AI tools for code quality, and optimize application performance while collaborating closely with teams.

The Senior Product Manager will lead the pricing and valuation engine, overseeing ML modeling, pricing systems, and improving valuation accuracy while managing cross-functional roadmaps and execution.

Co-found and lead a stealth startup building an agentic AI platform embedded in CAD tools to automate geometry updates, feature-tree edits, and cross-tool workflows. Drive product, engineering, and commercial strategy, hire the founding team, and develop a defensible data capture and automation stack for industrial CAD workflows.

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.

The Data Scientist will develop predictive models, analyze geophysical data, and collaborate with geoscientists to enhance exploration programs, focusing on mineral deposits.

Lead RWE study design and execution: develop protocols, statistical analysis plans, and R/SQL programs to produce analysis-ready datasets, tables, and figures; apply causal inference, time-to-event, and predictive methods; collaborate with scientists and stakeholders to deliver RWE insights.

The Principal Applied Scientist will lead the development of advanced computer vision and ML systems, optimizing solutions for real-time performance on edge devices and ensuring reliability in dynamic environments.

Lead end-to-end design and registration of agricultural soil carbon projects, interpret and implement VCS methodologies, design soil carbon sampling and GHG measurement strategies, prepare and defend project documentation, embed methodological rigor into products and processes, train staff, advise leadership on risk and strategy, and represent Perennial in registries and industry forums.