Top AI & Machine Learning Jobs

Develop novel AI and machine learning methods for protein interaction prediction, antibody and minibinder design, affinity prediction, and developability optimization. Design rigorous benchmarks, analyze large experimental datasets, contribute production-quality code and data, deliver models and technical reports, and provide technical leadership and mentorship. Collaborate with wet-lab scientists, external partners, and interdisciplinary teams while communicating research findings through publications, presentations, and scientific discussions.

The faculty member will teach undergraduate and graduate courses, mentor students, develop an extramurally funded research program in physical AI, and contribute to curriculum innovation, shared governance, and professional service. Associate and full professors will also lead major research proposals and center activities. Research areas include multimodal perception, physical dynamics, learning, control, decision-making, robotics, and autonomous systems.

Lead the product strategy and execution for LawnStarter’s consumer and Pro AI agent experiences. Own conversational AI, agent actions, customer-to-Pro messaging, human handoffs, workflow integrations, external AI agent access, evaluations, and guardrails. Ship reliable AI capabilities that resolve issues, complete bookings and service changes, improve productivity, and increase retention. This individual contributor role requires cross-functional leadership across engineering, applied science, design, data, support, and operations.

Leads enterprise Key Drivers Analytics and an Associate Director team delivering advanced analytics across pharmaceutical business priorities. Owns analytics roadmaps, methodologies, governance, modeling standards, talent deployment, and globally distributed delivery. Directs multivariate analyses, segmentation, diagnostics, scenario modeling, validation, insight generation, and executive recommendations. Partners cross-functionally to translate evidence into measurable business actions while ensuring reproducibility, compliance, responsible AI, and scalable analytical solutions.

Designs, deploys, and operates secure cloud and hybrid infrastructure for enterprise AI workloads. Responsibilities include container orchestration, GPU-enabled compute, APIs, microservices, CI/CD, infrastructure as code, MLOps, model serving, monitoring, data platform integration, and AI governance. The role partners with architecture, cybersecurity, data, and application teams to establish scalable AI platforms and support AI agents and models across business and manufacturing systems.

Supports the development of enterprise AI products by identifying opportunities, designing agentic workflows, authoring product and technical specifications, building prototypes, and collaborating with engineers through product release. The role focuses on applying AI, machine learning, process mining, APIs, context engineering, and evaluation methods to business-critical transactional systems.

Owns the enterprise strategy, roadmap, governance, service delivery, and adoption of Microsoft Copilot Studio and agent capabilities. Evaluates AI features, licensing, costs, security, compliance, and operational readiness; establishes governance and operating models; develops enablement, training, documentation, monitoring, and administration processes; and leads cross-functional initiatives supporting scalable enterprise AI adoption.

Leads responsible AI and automation adoption in local government by identifying operational improvements, evaluating tools, configuring workflows, managing pilots, training staff, and supporting sustained implementation. Coordinates custom development requirements, user testing, privacy and security reviews, data quality, ongoing ownership, and performance tracking. Collaborates with departments, IT staff, developers, leadership, and partner governments to improve services while managing risks and adoption barriers.

Develop and support AI-powered applications and automation solutions using Python, React JS, REST APIs, and enterprise integrations. Create and optimize prompts for LLMs, build user interfaces, integrate AI services, and participate in testing, troubleshooting, and application support. Collaborate with business and technology teams to deliver generative AI solutions. The role is intended for recent graduates with foundational AI, software development, and prompt engineering knowledge.

Leads an eight-person engineering team building AI agents, conversational analytics, data intelligence, voice agents, and their shared context graph and data platform. Owns technical strategy, architecture, delivery, hiring, reliability, security, tenant isolation, evaluation systems, and agent safety. The role remains hands-on, involving prototyping, coding, debugging, architecture reviews, production monitoring, and continuous improvement. Partners with product, design, customers, and forward-deployed engineering to turn freight-industry needs into scalable AI platform capabilities.