Top AI & Machine Learning Jobs

Develop and implement statistical, machine learning, predictive, and optimization models to solve business challenges. Design data-driven experiments, prepare and validate structured and unstructured data, create visualizations, and communicate findings to technical and non-technical stakeholders. The role also leads adoption of new data science techniques and supports continuous improvement of organizational practices.

Tenure-track faculty member developing an impactful robotics and AI research program, publishing high-quality research, securing external funding, mentoring students, and teaching undergraduate and graduate electrical and computer engineering courses. Responsibilities include curriculum development, interdisciplinary and industry collaboration, university and professional service, and advancing inclusive excellence. Candidates must hold a Ph.D. in electrical and computer engineering or a related field by the September 2027 start date, with demonstrated research potential and commitment to teaching and inclusive academic engagement.

Lead the design and implementation of production agentic AI systems for enterprise compliance. Responsibilities include multi-agent orchestration, RAG and memory systems, stateful Temporal workflows, evaluation and safety frameworks, OCR and document understanding pipelines, and AWS infrastructure. The role requires hands-on Python engineering, LLM application development, distributed systems expertise, and end-to-end ownership in an in-office San Francisco startup environment.

Designs, develops, tests, deploys, maintains, and enhances machine learning and AI solutions for healthcare. Responsibilities include managing ML codebases and pipelines, collaborating with clinical and research teams, implementing scalable workflows on HPC resources, reviewing code, troubleshooting models and data analysis, supporting publications, and developing reliable production services. The role also involves technical leadership, system debugging, on-call support, and cross-functional collaboration within the Innovation Office.

Annotates data accurately according to project guidelines, performs quality checks, provides feedback on annotation tools and processes, collaborates with project teams, maintains efficiency, and reports issues for resolution.

Leads The Bancorp’s enterprise AI and intelligent automation strategy, roadmap, governance, operating model, and delivery portfolio. Oversees AI-enabled workflows involving machine learning, NLP, generative AI, document intelligence, and agentic capabilities while ensuring security, compliance, model risk management, data governance, and regulatory alignment. Partners with executives and cross-functional stakeholders, evaluates vendors and platforms, measures business value, and builds the organization’s AI and automation capabilities through leadership, change management, adoption, and talent development.

Build and operate scalable data pipelines, evaluation frameworks, and production AI/ML/NLP models. Own the full lifecycle from data collection and transformation through training, deployment, monitoring, and continuous improvement. Develop robust tooling, observability, and quality checks while collaborating with product and engineering to integrate AI capabilities into user-facing features. Work pragmatically in a fast-moving startup environment and translate business needs into effective data and machine learning solutions.

Lead end-to-end Litify AI implementations for legal clients. Design Salesforce-based AI agent workflows, conduct requirements discovery, configure and deploy solutions, advise clients, define success metrics, and drive adoption. Partner with project managers, sales, engineering, customer success, and product teams while owning technical architecture, documentation, delivery outcomes, and client feedback. The role requires strong Salesforce implementation expertise, AI agent and LLM experience, prompt engineering, and client-facing consulting skills.

Lead the architecture, development, and deployment of scalable AI-powered backend systems. Design APIs and inference workflows, fine-tune and productionize LLM and transformer models, establish MLOps and governance standards, and evaluate AI technologies. Mentor engineers, guide cross-functional technical initiatives, improve system reliability and performance, and shape the organization’s AI strategy and roadmap.

Leads enterprise AI and automation deployments from validated prototypes through secure, supported production. Owns the operating relationship between AI and IT, including governance, security, architecture standards, data access, vendor strategy, monitoring, support, and operational resilience. Manages technical teams, budgets, staffing, career development, and deployment across operating brands while evaluating emerging AI technologies and recommending practical business applications.