Top Remote Machine Learning Jobs in Hartford, CT

Lead and manage the underwriting and credit risk model validation team, perform hands-on independent validations of complex ML models, assess data integrity and performance, identify and remediate model weaknesses, partner on MRM framework improvements, and coordinate with audit, compliance, and controls to meet regulatory standards.

Owns the lifecycle of AI-powered analytics products supporting clinicians, from requirements and discovery through production and maintenance. Partners with data scientists, engineers, clinicians, and executives to define roadmaps, prioritize trade-offs, establish data contracts and SLAs, validate model results, track performance, and demonstrate ROI. Leads Agile scrum teams and drives cross-functional delivery in complex healthcare environments.

Lead long-term technical strategy and execution across multiple teams, architecting and evolving foundational frontend/backend systems and platforms at massive scale. Drive AI/ML adoption, solve ambiguous, high-impact problems, remain hands-on in critical system design and implementation, and align senior leaders on roadmaps and engineering standards.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Own the technical sales process from prospecting through post-sales, designing customer solutions with Cloudera technologies, delivering demonstrations and presentations, partnering with account managers, advocating for customers, and supporting upselling and renewals. The role requires enterprise pre-sales experience, cloud and data technology knowledge, strong communication, business requirements discovery, and customer-facing technical evangelism.

Lead and transform the Fraud Intelligence Team by designing scalable operating models, QA and measurement frameworks, and talent programs. Drive labeling quality, operational metrics, and fraud prevention impact; convert frontline fraud observations into insights for Product, R&D, Analytics, and GTM; leverage AI, automation, and tooling; and serve as a cross-functional fraud subject-matter expert while developing early-career talent and measurable business outcomes.

Lead the design and implementation of critical Safety AI initiatives, focusing on real-time perception systems for edge devices and optimizing models for production deployment in safety-critical environments.

Lead strategy and execution for enterprise and mid-market GTM across multi-unit restaurant brands. Drive C-suite engagements, modernize sales motions, scale AI-powered forecasting, partner with Product/Engineering, and represent Toast in industry forums to win large, complex contracts.

Lead strategy and execution to attract, engage, and retain a global community of Pluralsight authors. Build author communications, engagement programs, communities, recognition, and events. Elevate author visibility (Author Fellows), integrate author expertise across Sales, Marketing, Customer Success, Product, and Learning Experiences, and lead a multidisciplinary team to drive measurable business impact.

You will execute and improve insurance workflows, analyze operational efficiency, collaborate with product teams, and support onboarding and documentation efforts.

Lead and scale MEDHOST’s software engineering organization, overseeing product delivery, modernization, security, reliability, scalability, and operational performance. Develop technology strategy and architecture roadmaps while driving AI-first transformation across products, engineering workflows, and enterprise operations. Establish performance metrics, govern technology investments, manage strategic initiatives, and advise executives on emerging technologies, risks, and opportunities. The role also requires implementing generative AI, machine learning, and AI governance within healthcare software environments.

Lead a global product team building automation-first, AI-assisted investigation and agent-facing tooling for AML, KYC, EDD, and sanctions screening. Define roadmap, metrics, vendor strategy, and regulatory controls to improve investigation quality, cycle time, and operational efficiency while ensuring security, privacy, and auditability.

Lead the strategic roadmap and business integration of CVS Health’s Clinical Insights Engine across screening, diagnosis, quality measurement, or care management use cases. Partner with platform product managers, clinical leaders, business owners, and technology teams to align clinical needs with scalable platform capabilities. Drive adoption, value realization, KPI monitoring, business cases, and continuous product improvement while ensuring measurable clinical and financial outcomes.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Supports responsible AI governance across the AI lifecycle by maintaining use case and model inventories, risk assessments, model cards, control evidence, audit documentation, transparency records, and remediation tracking. Translates regulatory and policy requirements into practical processes, coordinates cross-functional reviews, evaluates AI risks and controls, and communicates technical governance information to legal, compliance, audit, business, and executive stakeholders.

Review, label, and QA datasets for AI/ML training; maintain trackers, databases, and dashboards; follow annotation guidelines and SOPs; prepare and clean data; document processes; collaborate to resolve data queries while ensuring confidentiality and timely delivery.

Own the vision, roadmap, backlog, and outcomes for data products delivered by data science, AI engineering, and intelligent automation teams. Translate business problems into AI and automation initiatives, prioritize investments, evaluate emerging technologies, and lead pilots through production. Partner with stakeholders and agile delivery teams, validate data and model performance using SQL, ensure responsible governance and scalability, and communicate outcomes to technical and executive audiences.

Partner with healthcare clients to discover, design, and deliver production-grade AI/LLM solutions. Architect cloud-native systems, build and deploy ML/LLM applications, prototype rapidly, troubleshoot distributed systems, and lead client engagements to drive measurable business outcomes while collaborating across product, platform, and engineering teams.

Lead B2B activation marketing to drive patient starts from commercial referral channels by building scalable systems, attribution frameworks, and repeatable playbooks. Implement MarTech and data-driven strategies, run A/B and incrementality tests, automate campaign execution using AI/ML and LLM tools, and templatize activation campaigns while managing and growing a cross-functional team.

Lead technical project success for enterprise AI infrastructure engagements. Collaborate with engineers, clients, and account leaders to capture requirements, decisions, dependencies, risks, and tradeoffs. Track constraints involving security, compliance, data sovereignty, procurement, and restricted environments. Maintain project visibility, align deliverables with business objectives, resolve issues, support implementation-to-operations handoffs, and identify expansion and renewal opportunities. Translate complex technical concepts for engineering, business, and executive stakeholders.

Lead the vision, strategy, roadmap, and global execution of AI-powered learning and workforce skilling products. Manage and mentor product managers, collaborate with engineering, design, research, marketing, and customer teams, and drive products from customer insight through launch and scale. Build AI-native experiences, improve product adoption and metrics, foster inclusive team practices, and deliver measurable outcomes for millions of learners.

Analyze business processes, data quality, and datasets to identify AI and automation opportunities. Translate business requirements into AI/ML use cases, collaborate on model development, evaluate model performance, and deliver dashboards and reports. The role also supports data validation, AI solution monitoring, emerging technology research, governance, compliance, responsible AI, prompt engineering, and generative AI initiatives while partnering with business, data science, engineering, and product teams.

Conduct prospect research to identify and prioritize high-value individual and institutional donors. Develop donor profiles, relationship insights, predictive machine learning models, graph database capabilities, and agentic AI solutions for prospecting, risk analysis, and pipeline placement. Evaluate internal and external data, optimize analytical models, identify fundraising trends, and translate findings into donor engagement recommendations. Collaborate with technical and development teams while supporting adoption of AI tools and coaching others.

Own the full B2B sales cycle from prospecting and qualification through negotiation, closing, account expansion, renewals, and post-sale relationship management. Build trusted customer partnerships, conduct site visits, represent the company at industry events, and collaborate with leadership, product, and design teams to incorporate customer feedback. The role is remote, focused on U.S. time zones, and requires significant domestic and international travel.