Top Remote Machine Learning Jobs in Hartford, CT

Lead product strategy, requirements, roadmap, and AI capabilities for Honeywell Forge cloud applications serving utilities. Conduct customer and competitive discovery, translate utility workflows into product investments, define commercial opportunities, and partner with engineering to prioritize and deliver cloud-native B2B software. The role focuses on AI for grid operations, DER management, rate design, and utility program performance while ensuring measurable operational value.

Own the global consumer engagement and personalization domain across digital channels. Assess current capabilities, define multi-year strategy and roadmap, recommend personalization infrastructure investments, and translate priorities into shipped products. Partner with engineering, data science, design, marketing, legal, and regional teams to deliver scalable experiences. Establish metrics, run cross-market experiments, optimize performance, and make global versus localized decisions. Influence executives, mentor product managers, and apply AI, identity resolution, and generative AI to personalization.

Manage the AI opportunity roadmap for Risk Services, prioritizing use cases, coordinating internal data science teams and external vendors, translating business needs into requirements, and supporting AI governance, compliance, explainability, auditability, implementation, adoption, and benefits realization. The role focuses on business outcomes and solution delivery rather than hands-on model development.

Designs, develops, deploys, maintains, and optimizes ETL processes and cloud-based system integrations for healthcare data warehousing and business intelligence. Works with DHA and Cerner inpatient and outpatient data, develops database procedures, validates migrations, performs data mapping and modeling, and supports data science and machine learning teams. The role also documents processes, tunes performance, captures client requirements, and manages data transformation initiatives.

Own and develop SandboxAQ’s intellectual property function, including patent portfolio strategy, invention harvesting, prosecution, lifecycle management, outside counsel oversight, freedom-to-operate analyses, trademark clearance, and trade secret programs. Partner with scientists, engineers, and business teams to protect innovations, inform product strategy, support transactions, and build scalable IP processes in a fast-growing AI-focused company.

Lead technical strategy and execution for production clinical AI across a portfolio: set AI direction, ensure regulatory and governance alignment, partner with product and engineering, improve model evaluation/monitoring and production reliability/cost/latency, promote reusable model patterns, and hire/coach data science leaders to scale clinical AI capabilities.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Own the research-to-production pipeline: harden training/evaluation workflows, build packaging/deployment tooling, design release gates, optimize inference and serving for latency/throughput, establish benchmarking and validation, and instrument feedback from production to accelerate research iteration.

Lead enterprise data security architecture to protect sensitive data across its lifecycle. Define strategies for encryption, key management, tokenization, masking, DLP, classification, database security, and Zero Trust. Advise execs and engineering on secure design patterns for data platforms (e.g., Starburst), cloud/on-prem systems, APIs, data pipelines, and AI/ML workloads. Develop roadmaps, evaluate technologies, mentor staff, and drive secure-by-design adoption across the organization.

Leads and scales the post-sale customer success organization, overseeing customer retention, expansion, adoption, renewals, and customer outcomes. Manages 20 or more Customer Success Managers and Leads, develops scalable lifecycle processes, integrates AI into customer success operations, and partners cross-functionally on product and revenue strategy. The role also manages strategic accounts, international expansion across Mexico and Latin America, team development, performance metrics, customer advocacy, and operational excellence.

Manage paid media strategies and campaigns across search, social, display, and programmatic channels. Advise clients using integrated paid, organic, and analytics data; oversee campaign performance, keyword research, ad copy, landing page recommendations, and presentations. Build client relationships, mentor account associates, collaborate with SEO and data teams, and use AI to improve workflows and outcomes.

Develop and lead paid media strategies across search, social, display, and programmatic channels. Manage campaign strategy, performance analysis, testing, optimization, and integrated paid and organic recommendations. Consult with clients, present results, build relationships, mentor account associates, and identify data-driven growth opportunities. Use AI tools to improve workflows and contribute insights across the team.

Lead strategy to define, measure, and evolve Solution Engineer and Cloud Solution Architect excellence for Microsoft Security. Use data, AI-powered analytics, and customer insights to identify performance drivers, design capability strategies, advise senior leaders, and drive field transformation. Build governance, risk remediation, and scalable enablement programs while partnering across engineering, product, sales, and enablement to measure impact and continuously improve outcomes.

Design, build, and deploy production-ready intelligent solutions using machine learning, deep learning, generative AI, and large language models. Develop RAG pipelines, integrate AI services, manage model deployment and MLOps workflows, and apply strong software engineering practices. Collaborate with engineering, product, and data teams in a distributed environment to create scalable, reliable, responsible AI-powered products.

Designs statistical analysis plans and validates machine learning models using rigorous performance, calibration, uncertainty, subgroup, fairness, and longitudinal analyses. Applies biostatistical methods to healthcare data, documents assumptions and limitations for auditability and regulatory readiness, and translates complex findings into clinically meaningful insights. Collaborates with engineering, machine learning, data, clinical, and product teams.

Leads technical strategy and product adoption for major Retail and CPG enterprise accounts as Databricks’ primary technical voice. Partners with account executives, guides customers through data and AI transformations, builds technical champions, aligns solutions to business strategies, and mentors team members. Requires extensive pre-sales, big data, cloud, data science, programming, and production data systems experience.

Owns CareSource’s EDI platform vision, roadmap, backlog, and delivery. Translates healthcare, regulatory, and integration requirements into technical specifications; partners with engineering, architecture, QA, DevOps, trading partners, and business teams; coordinates releases and Agile delivery; monitors transaction performance, defects, SLAs, and platform telemetry; drives data quality, observability, automation, compliance, documentation, and continuous improvement across EDI capabilities.

Designs, integrates, tests, maintains, and upgrades complex IT systems across hardware, software, and security domains. The role validates system compliance, diagnoses issues, recommends improvements, and supports secure, reliable mission-critical environments. Responsibilities also include working with unstructured data using open-source tools, cloud computing, machine learning, and data visualization technologies, while collaborating with cybersecurity teams.

Leads the See & Scout engineering organization across software, data, machine learning, and robotics. Owns technical strategy, architecture, and multi-year roadmaps for scalable cloud, distributed data, edge, and machine learning platforms. Oversees the full data and ML lifecycle, production delivery, operational excellence, and customer-focused agricultural intelligence capabilities. Recruits and develops engineering leaders, partners cross-functionally, and aligns stakeholders across Blue River and John Deere.

Build and lead Nebius’s federal affairs function in Washington, D.C. Develop policy strategy across AI regulation, trade, energy, infrastructure, and national security; establish bipartisan relationships with Congress and executive agencies; represent the company in federal initiatives and coalitions; assess regulatory risks; coordinate with legal, communications, and infrastructure teams; manage outside lobbying partners; and hire staff as the function scales.

Develop and test AI software using large datasets, algorithms, and statistical analysis for industrial applications. Collaborate with machine learning and data engineers to build integrated AI/ML solutions, evaluate performance, monitor industry trends and regulations, and present progress to leadership and stakeholders. The internship offers hands-on experience, mentorship, and exposure to practical AI innovation.

Develop and test AI software for industrial applications using Python, JavaScript, and C++. Evaluate data, statistics, and algorithms; collaborate with machine learning and data engineers; support end-to-end AI/ML integration; monitor industry trends and regulations; and present progress to leadership and stakeholders.

Lead research, architecture, and production deployment of large-scale algorithms for budget pacing, bid optimization, and marketplace balancing in Yahoo’s DSP. Apply control theory, optimization, and machine learning to real-time systems, while establishing AI-augmented research and engineering workflows. Own multi-quarter initiatives, define evaluation frameworks, guide technical strategy, collaborate with product and engineering leadership, mentor scientists and engineers, and communicate complex research and architectural decisions to executives.

Lead the definition and evolution of cybersecurity technology platform and service offerings for cyber defenders and CISOs. Drive requirements through software and service lifecycles, deliver differentiated offerings to market, and guide cross-functional teams toward consistent, high-quality execution. The role requires deep expertise in at least two cybersecurity domains, managed services experience, strong communication skills, executive presentation ability, and awareness of AI’s impact on cyber defense.

Lead the vision, strategy, roadmap, backlog, delivery, adoption, and lifecycle management of an enterprise AI platform. Manage three direct reports and collaborate across technology, cybersecurity, risk, legal, compliance, data, and analytics. Ensure secure, scalable, governed, and responsible AI capabilities while translating business and technical priorities into measurable product outcomes. Drive stakeholder alignment, platform adoption, continuous improvement, executive communication, and team development in a highly regulated environment.