Artificial Intelligence Jobs in Newark, NJ

As a Sr. Product Manager - AI, you will drive product strategy, engage with customers, define product metrics, and collaborate with teams to enhance product performance.

Lead the vision for Guardian's digital experience and design system, leveraging AI technologies to enhance user engagement and collaboration while promoting design best practices and team development.

The Director will develop partnerships for Energy Management and AI while leading a team, driving profitability, and enhancing customer relations.

The Full-stack Developer will build and deploy AI automation solutions, integrate various technologies, and develop the frontend and backend components for efficient workflows.

Develop and maintain scalable APIs and Kubernetes environments for AI solutions, collaborating with teams to ensure robust and secure deployments.

Lead the architecture and design of AI systems, integrate and fine-tune models, manage multi-agent frameworks, and collaborate with teams for deployment and observability.

As a Senior AI Engineer, you will design and implement AI solutions, collaborate with teams to define success metrics, and iterate on AI model performance.

The AI / Machine Learning Engineer will design, build, and deploy ML models for image classification, fraud detection, and data pipelines, while collaborating with product and engineering teams.

Drive presales efforts for an AI-driven eProcurement SaaS solution. Engage with clients, demonstrate product capabilities, and support the sales process to ensure successful implementations.

The Full-Stack Developer will design and deploy AI-focused tools for automation, collaborating with teams to optimize prompts and outputs, while mentoring juniors in a dynamic environment.

The Full-Stack AI Product Developer will manage projects from research to deployment, focusing on building AI-driven tools and enhancing user engagement within a healthcare context.

Lead the architecture and implementation of generative AI platforms for healthcare payers, focusing on cloud solutions, system design, and client engagement.

The role involves leading the development and deployment of Generative AI solutions across commercial functions, ensuring alignment with governance frameworks and fostering cross-functional collaboration for business value.

Lead the design and delivery of intelligent, data-driven solutions in the Salesforce ecosystem, overseeing AI/ML integration and deployment of autonomous agents.

The VP Global Head of Data Analytics, Data Science, & AI strategizes, leads teams, manages projects, and drives innovation in data-driven decision-making, governance, and technology integration.

The Embodied AI Researcher will conduct research on robotic foundation models and embodied intelligence, collaborating with cross-functional teams and integrating robotics products.

Drive analytics and machine learning solutions as a product owner, collaborating with stakeholders and leading Agile product planning and roadmaps.

The AI Architect will lead the design of an agentic AI platform, optimize ML models, and ensure system integration while providing technical leadership.

Lead design strategy for AI Agentic SaaS product, focusing on user-centric design and collaboration with cross-functional teams. Oversee research, design execution, usability testing, and mentor design talent to enhance product experience.

Lead market research and consumer insights in CPG, translate data into actionable insights, and guide product development in collaboration with cross-functional teams.

The AI Product Transformation Manager will develop AI product strategies, manage stakeholder communication, oversee product delivery, and collaborate across teams to enhance AI capabilities for business efficiency.

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.

Responsible for designing and maintaining cloud infrastructure with a focus on Kubernetes, building teams for release management, and ensuring application security and cost optimization.

Lead the Data AI and BI teams to drive data strategies, optimize AWS solutions, and manage AI/ML lifecycle, ensuring compliance and innovation.

Design, develop, and maintain full stack applications, integrate AI/ML models, and ensure code quality and performance.