Top Senior Machine Learning Jobs in Hartford, CT

Lead Tekmetric's API product strategy and roadmap for the SaaS platform. Own API lifecycle (contracts, versioning, documentation), drive developer experience and adoption, identify integration opportunities, lead generative AI initiatives, perform user research and analytics-driven prioritization, collaborate across design/engineering/sales, train internal teams, and measure business impact.

The role leads the design and delivery of AI-powered technology to enhance productivity in claims operations, managing cross-functional teams to achieve strategic objectives.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Lead and grow a global engineering team building endpoint visibility, prevention, and on-device ML across Windows, macOS, and Linux. Own roadmap and delivery, direct model development and telemetry, drive cross-platform protection parity, coordinate with product and partner teams, and represent the team externally through research and conferences.

Lead the vision and execution of data product roadmap; translate business needs into epics and acceptance criteria; partner with data engineering and analytics; run agile ceremonies and manage backlog; champion data-as-a-product; scope and pilot AI/ML capabilities; present roadmaps and business cases to leadership.

Full-cycle territory sales role selling Greenway Health's EHR, RCM, and AI-driven healthcare solutions. Responsibilities include prospecting, lead generation, demos, RFP management, proposal configuration, negotiation, closing, maintaining Salesforce, meeting quota, and providing market feedback. Role requires heavy travel (50–75%) and collaboration with internal solutions consultants to deliver value-based technology and revenue cycle capabilities to ambulatory healthcare clients.

Conduct research and develop identity and probabilistic-matching models for Netflix's ad-supported tier. Apply ML and statistical methods, ensure privacy-preserving solutions (differential privacy, anonymization), prototype and deploy production models, deliver datasets and tools, and partner with product, engineering, and business stakeholders to measure and drive impact.

Design, build, and operate core AI capabilities and reusable model integrations for an enterprise platform. Integrate foundation models into production, optimize performance and reliability, prototype new techniques, and support scalable backend services and distributed AI systems in collaboration with cross-functional teams.

Own end-to-end product development for AI/ML revenue cycle solutions: define vision and roadmap, write specs and user stories, prioritize backlog, work closely with data scientists and engineers, drive agile delivery, ensure quality, and measure product performance with stakeholders.

Lead and mature Omada's enterprise privacy program, manage HIPAA compliance and incident response, embed privacy-by-design across products, conduct privacy risk assessments and vendor due diligence, advise on consumer privacy and AI governance, support interoperability/HIE participation, and deliver privacy training and guidance across the business.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

Provide legal counsel on privacy, AI, identity, and advertising technology; embed privacy by design with product and engineering teams; draft and negotiate privacy provisions and DPAs; advise on cross-border transfers and SCCs; run privacy and AI risk assessments; support incident response; create scalable legal playbooks and AI-enabled workflows; represent Yahoo in industry standards bodies.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

Drive technical wins for enterprise financial institutions by scoping solutions, leading discovery (MEDDPICC), tailoring demos, building business cases, owning RFI/RFPs and POCs, and coordinating product/engineering to validate feasibility for fraud and financial crime prevention.

Build and maintain ML and generative AI tooling, training and inference platform services, model evaluation and testing frameworks, and APIs to expose ML products. Deploy and manage applications across the AI/ML SDLC, mentor teammates, and write production-quality code daily.

Lead enterprise AI platform automation across infrastructure provisioning, CI/CD, governance, observability, deployment, and lifecycle management. Build self-service capabilities for GenAI, data science, data engineering, and analytics workloads using Terraform, Kubernetes, cloud technologies, Python, and DevSecOps practices. Support agentic AI, event-driven architectures, distributed computing, and operational reliability while collaborating with engineering, architecture, governance, security, and business stakeholders. Provide technical leadership, design reviews, mentoring, and best-practice guidance.

Build and deploy production machine-learning systems within client environments, covering data discovery, modeling, validation, deployment, scheduling, monitoring, and retraining. Develop forecasting and detection models for imperfect time-series data, establish honest evaluation and KPI frameworks, and ship usable APIs or interfaces. Work directly with client IT and data teams through discovery, demos, and feedback cycles. The role also involves data engineering, software development, basic cloud and DevOps work, and advising clients when ML is not appropriate.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

The Director of Product Management will oversee the product lifecycle for AI products, focusing on customer collaboration, rapid prototyping, and product strategy. The role involves leading product teams, driving execution, and shaping the product culture.

The SAP Innovation Architect will design SAP automations, mentor engineers, and drive innovation in AI-driven SAP operations, while ensuring scalability and security in integrations.

Act as the technical lead in enterprise sales: run technical discovery, design and deliver customized demos and POCs, assess API/cloud/model fit, address technical objections, support contract negotiations, and relay product feedback to engineering while staying current on AI/ML trends.

Lead strategy and build 0->1 AI products that streamline complex healthcare workflows across providers, pharmacies, patients, and pharma partners. Own roadmap, requirements, metrics, and product performance; partner with engineering, data, clinical, and commercial teams to launch and iterate AI-enabled solutions that drive adoption and measurable business and patient outcomes.

Lead backend architecture and implementation for scalable, reliable cloud-hosted web products. Mentor engineers, set standards, integrate agentic AI coding tools, design systems applying ML to large datasets, and balance customer-facing features with technical debt and performance.