Top Machine Learning Jobs in Hartford, CT

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

Develops and deploys digital twin simulation services, optimization algorithms, and analytics for water and wastewater networks. Configures and calibrates hydraulic models, analyzes sensor data, manages large datasets, and translates analytical findings into practical solutions for engineers, analysts, and utility decision-makers. Collaborates with multidisciplinary teams on water project delivery and participates in company volunteer activities.

Leads CVS Health’s technology assurance function across IT and cybersecurity audit, emerging AI risk assurance, and ERP implementation advisory support. Sets audit strategy, oversees executive directors and their teams, evaluates technology governance and controls independently, coordinates established and emerging risk coverage, and reports findings to senior leadership, the CAE, and Audit Committee. Builds organizational capability, communicates complex technology risks clearly, and advises ERP and AI governance forums while preserving Internal Audit independence.

Lead technical strategy for a 50–150+ engineer organization, establish architecture and engineering standards, drive delivery, and partner with executives on technology investments. Embed production-grade generative AI, LLMs, agentic workflows, and ML automation into engineering. Own AI platforms, distributed systems, cloud-native backend architecture, modernization initiatives, microservices migrations, and engineering transformation while ensuring scalable, reliable outcomes.

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.

Supports data and analytics projects by designing ETL processes, developing data pipelines, integrating and validating data, and improving data quality. Creates Power BI reports and dashboards, troubleshoots data and storage issues, and helps enhance data warehouse and analytics solutions. The intern also explores AI-enabled tools, cloud platforms, and modern data engineering practices while collaborating with business partners.

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.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Evaluate AI model outputs on data science, statistics, machine learning, experimentation, and quantitative problems. Develop expert prompts, datasets, and reference solutions; identify statistical and methodological errors; and provide structured feedback to improve model performance. The role requires Python, machine learning, statistics, data analysis, experimentation, Pandas, and data modeling skills.

Build and deploy machine learning, NLP, and LLM-powered solutions at scale. Improve production model performance, reliability, and accuracy; develop datasets, metrics, tools, and experimentation frameworks; and use data to influence product strategy. Partner with Product, Engineering, and business stakeholders to drive AI innovation, while serving as a technical thought leader and mentoring other data scientists.

Leads customer R&D transformation engagements from pre-sales through delivery. Shapes scientific and technical challenges into AI architectures, product backlogs, MVPs, simulations, integrations, data pipelines, and production solutions. Partners with executives, researchers, engineers, product teams, and account teams to define outcomes, scope delivery, assess data and compute needs, and establish roadmaps. Develops reusable architectures and delivery playbooks while influencing Microsoft Discovery product direction and scaling AI-powered R&D solutions across industries.

Own product strategy, vision, roadmap, discovery, prioritization, prototyping, delivery, launch, and post-launch adoption. Conduct user and market research, use AI tools for synthesis and experimentation, collaborate with Design and Engineering, manage backlogs, define metrics, and communicate product direction across stakeholders.

Own the full enterprise sales cycle for Oversee’s leisure travel business, from prospecting through closing. Build relationships with OTAs, agencies, tour operators, and vacation providers; develop pipeline; identify target segments and use cases; refine positioning and sales strategy; lead complex stakeholder processes; and partner with Product and Engineering to convert market insights into a repeatable leisure sales motion.

Own AgentSee’s sales and go-to-market strategy as the first dedicated sales leader. Personally close early enterprise opportunities, refine the ideal customer profile, positioning, pricing, packaging, and sales process, and translate AI capabilities into measurable business value. Build repeatable sales operations and playbooks, provide market feedback to Product and Engineering, and eventually hire and lead the AgentSee sales organization.

Own customer onboarding by prioritizing integration work, developing Python and SQL data pipelines, automating repetitive processes, and leading technical customer calls. Translate CRM and fundraising data into model-ready formats, manage onboarding risks, document processes, support CSMs, and train team members. The role serves as Dataro’s US technical customer representative while collaborating with engineering in Sydney.

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.