Top Machine Learning Jobs in Hartford, CT

Build and own ClickUp’s AI evaluation systems, agent harness, self-improvement loops, model benchmarking, routing, and fallback strategies. Architect scalable backend and AI platform services for LLM deployment, orchestration, monitoring, logging, and automated evaluation. Improve reliability, privacy, security, and compliance while integrating AI features into the core product and collaborating cross-functionally.

Own company-level strategic initiatives, establish measurable goals, diagnose delivery risks, and recommend resource reallocations. Lead cross-functional transformation focused on go-to-market scalability, annual planning, quarterly reprioritization, monthly business reviews, and AI-enabled operational reporting. Partner with executives and functional leaders to improve the operating model, automate KPI tracking, communicate priorities, and increase organizational velocity.

Own the full enterprise sales cycle for Neuron7.ai’s AI-powered Service Resolution Intelligence platform. Responsibilities include prospecting, executive discovery, strategic account planning, ROI development, technical evaluations, negotiation, procurement, and closing new-logo enterprise deals. The role targets high-tech, manufacturing, and medical device organizations, requiring independent pipeline generation, accurate forecasting, executive relationship management, and collaboration with solution consultants, architects, product, and customer success teams.

Own regional enterprise revenue and go-to-market strategy for AI-powered field service solutions. Lead pipeline generation, forecasting, territory planning, major new-logo deals, and C-level relationships. Hire, coach, and retain Account Executives while driving disciplined sales execution across high-tech, manufacturing, and medical device industries. Lead strategic enterprise sales cycles and position Agentic AI and automation solutions for complex service operations.

Leads Cohere’s global Customer Success, Services, and Technical Support teams, driving adoption, customer experience, lifecycle strategy, and executive-level customer advocacy. Defines workflows and handoffs, coaches functional leaders, analyzes customer and support data, improves the customer journey, and influences product strategy. Partners with pre-sales, Product Management, and Machine Learning Engineering to represent customer needs and deliver value to enterprise AI customers.

Own strategy and execution for a gaming-oriented B2C mobile app focused on advertising, rewards, loyalty, and commerce. Responsibilities include roadmap and backlog management, analytics and A/B testing, conversion optimization, user research, competitive analysis, product documentation, prioritization, and cross-functional collaboration with engineering, design, marketing, legal, operations, and support teams.

Own Carrum Health’s member and employer growth funnels, including landing pages, activation journeys, eligibility and sign-up flows, experimentation, attribution, and lower-acuity service-line launches. Partner with engineering, design, marketing, sales, care, compliance, and machine learning teams to improve conversion and access to specialty care. Lead a growth pod, build scalable content systems, use AI for rapid prototyping, and optimize responsibly within healthcare privacy and clinical guardrails.

Own product and research launch marketing from technical positioning through distribution. Translate AI research, training runs, and benchmarks into blogs, explainers, social content, landing pages, documentation, sales collateral, and campaigns. Engage technical communities, coordinate cross-platform launches, and use analytics to optimize reach, engagement, traffic, and adoption. The role requires strong technical writing, product marketing judgment, rapid execution, and experience communicating AI, ML, or developer tools to developers and enterprise audiences.

Leads the university’s information security architecture and engineering strategy, including cloud, network, endpoint, application, data, identity, and AI security. Establishes zero trust, DevSecOps, infrastructure-as-code, and security-as-code practices; oversees architecture, technology selection, compliance alignment, automation, and AI security initiatives. Builds roadmaps, secures funding, manages strategic initiatives, and leads, recruits, mentors, and develops security architects, engineers, and managers while advising executive leadership.

Provides technical leadership for architecture and evolution of large-scale distributed data platforms supporting Azure network telemetry. Designs streaming and batch systems, establishes reusable engineering patterns, drives cross-team technical strategy, and owns capabilities from design through production operations. Ensures scalability, reliability, security, performance, data quality, and operational excellence while mentoring engineers and influencing technical leaders. The role also involves architectural reviews, dependency management, risk reduction, and applying AI or machine learning approaches to operational systems.

Lead strategic sales of AI Workforce solutions, including Microsoft Copilot, AI agents, Viva, Windows 365, and Azure Virtual Desktop. Develop customer strategies, identify opportunities, build pipeline, conduct consultative business and technical conversations, and orchestrate internal teams and partners to close complex deals. The role requires expertise in technology sales, AI, forecasting, demand generation, stakeholder engagement, competitive positioning, and cross-selling across enterprise and regulated customers.

Leads architecture and production delivery of a near-real-time observability platform for large-scale AI supercomputers. Responsibilities include telemetry ingestion, processing, storage, querying, topology and health modeling, 1P/3P data convergence, AI-assisted anomaly detection, technician dashboards, repair validation, security, reliability, cross-team technical leadership, and mentoring.

Conduct life insurance underwriting audits and complex case reviews, assess mortality and risk data, make decisions within an $8 million authority, and evaluate automated underwriting models. Partner with engineering, data science, actuarial, compliance, and customer experience teams to identify rule gaps, improve audit processes, and maintain underwriting accuracy as automated systems evolve.

Leads advanced analytics, AI, automation, and scientific computing initiatives supporting pharmaceutical clinical development. Translates scientific and business requirements into scalable analytical products, software specifications, decision-support tools, and production automation. Partners across biometrics, clinical development, IT, and business teams; evaluates emerging AI technologies; improves regulated workflows; establishes value metrics; drives adoption and change management; and mentors technical talent.

Conduct research at the intersection of AI, cybersecurity, and computer systems. Formulate research questions, design experiments, build prototypes, evaluate AI and security methods, analyze real-world security data, and communicate findings through reports, presentations, and potential publications. The role combines research with practical engineering and offers mentorship while developing independence.

Leads Payment Integrity strategy and audit optimization by identifying claims-payment anomalies, reimbursement trends, provider behaviors, and new data-mining opportunities. Develops and tests audit concepts, evaluates financial and operational impact, and guides successful concepts through implementation across prepay and postpay processes. Optimizes existing audits, influences cross-functional stakeholders without direct authority, provides executive recommendations, and supports sustainable medical cost savings.

Build and evolve machine learning tooling and infrastructure for AI-powered clinical solutions, including automated prompt tuning, feedback loops, model benchmarking, experimentation, and evaluation. Partner with data science, clinical, software engineering, and product teams to develop scalable solutions, solve ambiguous technical problems, establish engineering standards, and provide technical mentorship without direct management responsibility.

Leads the enterprise Data Science and AI vision, strategy, roadmap, and global organization. Oversees production-grade machine learning, Generative AI, Agentic AI, predictive modeling, AI governance, deployment, monitoring, cost optimization, and responsible AI. Partners with executive, product, engineering, commercial, legal, operations, and customer success stakeholders to deliver scalable AI products, automation, improved customer outcomes, and measurable business value.

Designs and scales AI-driven security GRC automation, including compliance evidence collection, control testing, risk assessment, audit preparation, and workflow integration. Builds scripts, bots, APIs, and AI/LLM solutions; integrates GRC platforms with security and IT systems; establishes quality controls and guardrails; monitors automation risk and performance; and partners with technical and business stakeholders to improve security compliance maturity.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Develops AI agents, automation tools, predictive models, and decision-support solutions using structured and unstructured data. Leads AI projects from conception through deployment, evaluates analytical approaches, and collaborates with engineers, architects, product managers, and business stakeholders. Applies statistical and mathematical techniques, develops performance metrics and reports, communicates technical findings, and uses Python, SQL, and cloud technologies to solve complex business problems.

Own and scale Jellyfish’s security engineering program, including strategy, architecture, secure SDLC governance, AI security, threat modeling, vulnerability remediation, incident response, penetration testing, and bug bounty programs. The role combines hands-on software development with executive advising, cross-functional leadership, mentorship, and security risk management across SaaS infrastructure and customer-facing AI products.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Lead product strategy for AI-driven business automation and a monetized data-as-a-service offering. Build enterprise AI governance, agent operating models, evaluation standards, privacy controls, and responsible AI practices. Develop an AI champion network, prioritize automation opportunities, and measure productivity gains. Define data products, customer segments, pricing, packaging, and go-to-market plans while partnering across engineering, security, legal, privacy, risk, and business units.

Own post-sale relationships with referral partners, driving adoption, retention, renewals, expansion, and revenue growth. Serve as a strategic advisor, lead business reviews, resolve escalations, coordinate cross-functional teams, enable product usage, and advocate for partner needs. Maintain partner records and report on satisfaction, renewal, and revenue metrics while developing success strategies and playbooks.