Top AI & Machine Learning Jobs

Lead definition, development, and delivery of AI-powered features across the myQ ecosystem. Own AI product roadmap, translate customer needs into requirements, partner with engineering and data science, manage backlogs, measure impact, and drive cross-functional launches to grow subscription revenue and product engagement.

Lead planning, scoping, and building of agentic AI systems using LLMs, RAG, orchestration tools, and vector databases. Conduct experiments on reasoning, planning, and memory; build and optimize pipelines (e.g., LangChain, LangGraph, CAMEL); collaborate across product, engineering, and research; provide tooling, infrastructure, and deployment recommendations; and support end-to-end delivery and knowledge transfer for scalable assistant deployments.

Design, prototype, and deploy agentic LLM systems and RAG pipelines. Evaluate models and orchestration tools (LangChain, LangGraph, CAMEL), build/optimize pipelines, integrate vector databases, collaborate across product/engineering/research, and provide technical guidance for scalable GenAI deployments.

Lead and coach a data science team to design, develop, and deploy predictive and prescriptive analytics. Partner with business leaders to identify opportunities, drive adoption of models and insights, manage vendors, and establish data science methodology to deliver measurable business impact.

Lead and coach a data science team to design, develop, and deploy predictive and prescriptive analytics for business impact. Partner with senior leaders to identify opportunities, drive adoption of models, manage vendors, and establish data science methodology and best practices.

The role involves leading data science initiatives, managing and mentoring teams, and creating data-driven solutions to enhance business objectives at Chamberlain Group.

Lead Data Scientist partners with business leaders to identify opportunities, design, develop, and deploy advanced analytics and ML solutions. Responsibilities include data preparation, modeling, feature engineering, delivering insights and visualizations, establishing standards, and directing associate data scientists, contractors, and consultants to produce measurable business value.

Lead distributed engineering teams to build and operate real-time data serving, LLM orchestration, and ML pipeline infrastructure powering low-latency, personalized connected-home experiences. Own delivery, reliability, observability, drift detection, and model rollout; manage sprint cadence, hiring, and technical coaching while coordinating with product, architecture, AI/ML ops, and video intelligence teams.