Top AI & Machine Learning Jobs

Develop, deploy, and integrate machine learning and deep learning models for scientific and industrial problems (materials, chemistry, process optimization). Build data pipelines, feature engineering, model evaluation, and scalable production integrations. Collaborate with scientists, engineers, product, and customer teams to translate domain problems into AI solutions, support deployments, and communicate results. Conduct strategic research and stay current with AI/ML methods; periodic customer travel.

Build and operationalize machine learning and AI solutions for hospitality pricing, forecasting, and revenue management. Analyze large datasets, write Python and SQL to prepare and validate data, and partner with product and engineering to turn analyses into product capabilities. Apply modern AI techniques, including LLMs and AI coding tools, and communicate insights to stakeholders.

Own end-to-end clinical prediction models: design, train, evaluate, and ship models using physiological time series and EHR data. Define labels with clinical teams, build evaluation/backtesting and regression infrastructure, assess robustness and subgroup performance, support production deployment and monitoring, and contribute to validation and regulatory evidence.

Lead and scale Vibrant's data science, ML, and AI function: set strategy and governance, oversee applied research and production ML (especially NLP), ensure HIPAA-compliant deployments, partner with execs and engineering, recruit and mentor teams, and deliver measurable outcomes for crisis services and enterprise initiatives.

Lead end-to-end delivery of AI-first B2B SaaS product initiatives: write PRDs, define LLM-based features, run customer discovery, own vendor integrations, present roadmaps to execs, query data to validate decisions, and align distributed Engineering, Customer Success, Sales, and AI/ML teams.

Lead development of production AI agents across portfolio companies: identify recurring backlog patterns, design agent task hierarchies and orchestration, prototype end-to-end agents, technically lead teams, instrument agent performance, and scale playbooks across companies while earning CTO/CPO buy-in.

Lead and scale the Emerging Technology program, driving adoption of generative AI, ML, and data science across the company. Oversee program strategy, budget, vendor selection, compliance with SOX/FFIEC, metrics, and pilot governance. Advise senior leadership, deploy ML frameworks (TensorFlow, PyTorch, SageMaker, Azure ML), build data-driven products, and ensure secure, ethical, and enterprise-scale implementations.

Lead strategy, roadmap, and engineering for a firm-wide AI platform that captures and leverages firm knowledge. Build shared data/context layers, evaluate models and approaches, prototype and ship AI products, enable others to build on the platform, and manage a cross-functional team to drive measurable impact on sourcing, diligence, portfolio support, and firm outcomes.

Work with customers to discover high-value AI use cases, design and prototype LLM- and agent-based solutions, build demos and pilots, and support transition to production. Provide technical architecture, documentation, training, governance guidance, and hands-on implementation support across integrations, automation, and evaluation to enable secure, explainable, and measurable AI adoption.

Lead the technical vision and enterprise architecture for AI solutions. Design scalable, secure LLM and conversational AI deployment patterns, API integrations, and data architectures. Govern standards, collaborate with product, engineering, data, infrastructure, and security teams, and evaluate emerging AI platforms and technologies.