Top Senior Machine Learning Jobs in Hartford, CT

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.

The VP of Sales will drive enterprise adoption of AI-powered healthcare software, engage with stakeholders, and shape go-to-market strategies for new AI products.

The Senior AI Engineer role involves deploying AI solutions to extract structured data from medical charts, improving efficiency and ensuring compliance. Responsibilities include developing AI extraction pipelines, maintaining AI model production, and collaborating with cross-functional teams to integrate AI solutions into healthcare systems.

Lead the Performance ML team at MNTN, driving strategy and deployment of predictive models for ad technology, while managing, mentoring, and scaling engineering teams.

Lead Yahoo's Data Activation product area: define vision and strategy, partner with Data Science and Engineering, drive cross-vertical data activation initiatives, deliver measurable business impact, and mentor/manage product teams to execute on audience, personalization, and targeting use cases.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Lead Data Scientist responsible for creating ML-driven risk assessments and AI workflows within a SaaS security platform, ensuring effective decision-making and system reliability.

The Staff Technical Program Manager will lead complex product development programs, manage schedules, communicate risks, and advocate for changes required to address business shifts, while influencing teams and stakeholders through various initiatives and maintaining program metrics.

The Data Science Manager will lead and mentor a team of data scientists, drive data-driven decision-making across Stripe, and collaborate with various stakeholders. Responsibilities include managing projects, recruiting, and contributing to broader data science initiatives.

The Principal Architect will lead AI/ML solutions, mentor teams, and collaborate with clients to design and deliver scalable systems using Google Cloud technologies, ensuring compliance with ethical standards.

The Hyperscalers and Commercial Lead will develop technology-driven business strategies, drive customer adoption, and manage end-to-end sales processes while working closely with cross-functional teams.

The role focuses on leading editorial efforts to define industry narratives around energy infrastructure, translating regulatory changes into strategic content for executives, and influencing sales and positioning through high-impact communications.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The Senior Director leads research in Application Platforms & AI, guiding clients in AI strategy and market trends, while producing critical research content and engaging with clients directly.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

As a P&C Actuary, you will assess insurance risks, review regulatory compliance, support audit teams, and document findings while nurturing client relationships and contributing to practice development efforts.

Senior product engineer owning end-to-end product surfaces for a computer vision platform. Ship features from idea to production, prioritize roadmap, design UX details, integrate APIs, improve annotation and model-assisted labeling, and collaborate with engineering and users to drive product impact.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Define and drive the AI and data product roadmap for a regulated B2B SaaS platform. Identify and validate AI-first product opportunities, lead discovery and commercialization, partner with engineering and data science to deliver explainable, auditable AI capabilities, and enable AI across existing products. Engage customers and executives to prioritise use cases, measure outcomes, and establish repeatable launch and governance practices.

Develop, deploy, and operationalize analytical and ML/AI models for cybersecurity use cases. Collaborate with product and engineering teams to enable and migrate production workflows, work with databases and data architectures, create visualizations and reports, adopt new cloud orchestration and data virtualization technologies, and mentor junior cyber data scientists.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

Pre-sales technical lead for federal accounts who builds and delivers AI/ML and GenAI demos, designs compliant solutions (FedRAMP/DoD IL/NIST/FISMA), supports pilots/proofs, advises on data readiness and security, and partners with sales to drive federal adoption.

Lead strategy and roadmaps for platform offerings that support robotics and autonomous systems. Drive customer discovery, define requirements and metrics, coordinate cross-functional execution, ensure production readiness, and lead adoption, rollout, and stakeholder communication for platform capabilities.