Machine Learning Jobs in Jersey City, NJ

Lead the Client Services Program Manager to deploy business solutions in financial services, managing multiple client programs and ensuring high-quality service delivery.

Design, build, and maintain AI-driven workflows, data pipelines, and full-stack web applications to automate course creation and multimedia content processes. Apply ML, NLP, and generative AI to improve content quality, analytics, and operational efficiency; build APIs, CI/CD pipelines, dashboards, and integrations while collaborating with SMEs and cross-functional teams.

Lead client relationships, delivery, and account growth for analytics engagements. Define analytics roadmaps, scale pilots to long-term programs, present to executives, collaborate with sales, and manage teams solving CPG, Retail, and financial services problems using data science and ML.

The Principal Product Manager will define and drive the strategy for the Computer Vision Platform, managing product requirements and lifecycle while ensuring significant customer impact and adoption of AI-driven solutions.

Lead enterprise AI governance operations: own AI use-case intake, triage, risk assessment, platform deployment, board coordination, stakeholder reviews, policy implementation, reporting, and ongoing monitoring to ensure responsible AI use.

The postdoctoral associate will design systems for transactive energy communities, focusing on socio-technical energy behavior and algorithm implementation for mechatronic systems.

The Principal AI/Machine Learning Engineer will lead the adoption of AI/ML in manufacturing by defining use cases, driving implementation, and ensuring organizational readiness.

Lead global pricing strategy and modernization for wholesale and specialty insurance, driving analytics, AI/ML integration, pricing model governance, catastrophe and transaction-level pricing support, and talent development to improve underwriting performance and return on capital.

Lead North America digital and technology programs across multiple product and business teams. Define multi-year strategy, governance, and value realization; align senior stakeholders; manage interdependencies, RAID, vendors, and adoption; drive AI and product innovation while scaling delivery and change across the enterprise.

The VP of Product will lead CoreWeave's Research Training Stack, focusing on enhancing AI infrastructure, ensuring quality for pre-trained models, and connecting researchers with advanced cloud capabilities.

Senior AI leader responsible for defining enterprise AI strategy, prioritizing high‑value use cases across underwriting, pricing, claims and operations, building an AI organization, partnering with technology/data/risk teams, ensuring regulatory compliance, and driving adoption and measurable business outcomes.

The role involves leading analytics delivery to clients, managing relationships, ensuring account growth, and solving complex business problems through data science in various sectors, primarily CPG and Retail.

The VP of AI Software Engineering will lead AI-driven technologies for software quality improvement and platform reliability, oversee AI solutions design and delivery, mentor engineering teams, establish governance, and collaborate with stakeholders to integrate AI solutions in software development processes.

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.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

Lead and coordinate technical AI and digital transformation projects across data, model, and platform domains. Translate architecture into project plans, manage cross-functional dependencies, enforce CI/CD and observability, oversee testing and compliance (regulatory and security), create runbooks and incident response, and ensure audit-ready evidence and controlled production cutovers.

The Senior Solutions Engineer will manage the technical sales process, address customer needs, design solutions, and work closely with sales teams to meet targets while advocating for customer requirements.

The AI Engineer will analyze business processes for automation opportunities, design and maintain RPA solutions, and develop Intelligent Document Processing systems while collaborating with stakeholders and ensuring reliability of solutions.

The Principal Data Scientist will create scalable data solutions and machine learning models, collaborating with teams to drive innovation in the financial industry.

The Algorithmic Trading Senior Manager at FanDuel will lead the algorithmic trading team, focusing on developing automated trading strategies and optimizing capital utilization while managing risk and team operations.

Lead Data Science for Personal Lines (Homeowners, Auto) at Chubb. Oversee data engineers and scientists to develop pricing, underwriting, segmentation, lifetime value, and operational models. Drive AI adoption, partner with business leaders, shape hiring and upskilling, and deliver analytics products and insights to support strategic objectives.

Lead and deliver GenAI projects from research to production, collaborating with engineering and business partners. Design LLM-based solutions, drive multiple initiatives, mentor team members, present results to stakeholders, and realize measurable business impact.

Lead product ownership of the payment routing engine, intelligence layer, and integration platform. Define roadmap, partner with Engineering, Data Science, Risk, and Fraud to build API-driven connectors, routing logic, failover flows, and ML-based optimization to improve authorization rates, reduce costs, lower latency, and increase resilience at scale.

Lead strategy and roadmap for Payments and Fraud platforms, manage product managers, drive improvements in payment success, fraud mitigation, routing, reconciliation, and real-time monitoring. Align stakeholders across Risk, Compliance, Finance, and Data Science while delivering measurable growth, reliability, and cost reductions.

Lead strategy and delivery for an AI-powered claims decision-support and auto-adjudication platform. Define vision and roadmap, manage a team of product managers, partner with business, engineering, and data science, and drive adoption, impact measurement, and executive-level communication across a complex, matrixed enterprise.