Top AI & Machine Learning Jobs

Build and operate AI-native, full-stack products for sales, marketing, and revenue operations teams. Develop agent workflows, automations, integrations, and production applications for research, enrichment, account scoring, and other go-to-market needs. Collaborate with nontechnical users to understand workflows, test solutions, and improve products. Integrate systems such as Salesforce, Marketo, and Gong while making pragmatic build-versus-buy decisions.

Build and operate production AI agents, companions, and workflow automations across sales, finance, marketing, and property operations. Integrate Azure, Snowflake, SaaS platforms, and vendor APIs while managing evaluations, monitoring, security, human review, cost, and reliability. Partner with business users and executives to identify high-value opportunities, measure adoption and outcomes, train users, and maintain governance. The role requires strong backend engineering, applied LLM experience, integration expertise, and sound data-security judgment.

Build and deploy AI tools, automations, scripts, training materials, and dashboards that improve agency workflows and client engagements. Coach teams on AI-assisted processes, research emerging tools, prototype solutions, measure efficiency gains, support internal training, and collaborate with leadership and account teams. The role emphasizes practical delivery, experimentation, communication, organization, and cross-functional collaboration rather than research.

Develop and maintain AI-powered applications, agents, automations, and integrations for legal and operational workflows. Build LLM tools, RAG systems, APIs, and workflow automations using Python and/or JavaScript/TypeScript. Manage projects from prototype through deployment, evaluate AI performance, maintain secure integrations, and collaborate with attorneys, leadership, and technical teams to improve internal processes.

Principal Data Scientist supporting a U.S. Government customer by designing and implementing machine learning, data mining, statistical analysis, AI, and advanced analytics solutions. The role requires analyzing complex datasets, developing predictive and prescriptive models, using Python or R and database technologies, and providing technical expertise for mission-critical software and systems. It is based in Annapolis Junction with limited partial telework and requires an active or reinstatable TS/SCI with Polygraph clearance.

Optimize large-scale machine learning training systems across CPUs, GPUs, and accelerators. Responsibilities include benchmarking, distributed-training optimization, GPU kernel and framework development, end-to-end pipeline efficiency, numerical optimization, and training infrastructure. The role partners with ML researchers, quantitative researchers, HPC engineers, systems engineers, and hardware specialists to improve performance, scalability, utilization, reproducibility, and cost across on-premises and cloud environments.

Lead Mission Lane's AI operations strategy end-to-end: identify high-impact AI use cases for contact center operations, build business cases, evaluate vendors, sequence and drive cross-functional execution, establish governance, and measure outcomes in cost, quality, and customer experience.

Tenure-track Assistant Professor responsible for teaching introductory through advanced computer and information science courses, developing curricula, advising students, assessing learning, participating in governance and service, and maintaining an active scholarly research agenda. The faculty member will support accreditation, recruitment, student development, and inclusive excellence while adapting instruction for online and hybrid formats.

Director-level role focused on global operations, data, and artificial intelligence at Callaway Golf Company. The provided description includes company background, diversity information, and compensation, but does not specify detailed responsibilities or qualifications.

Own Matter Health’s AI platform strategy, architecture, governance, budget, and operations. Design secure tools and integrations for deploying AI agents and workflows, including MCP and RPA integrations. Establish development standards, monitoring, reliability, and incident-response practices while partnering with engineering, security, compliance, clinical, and operational teams. Evaluate vendors and platform investments, guide internal builders, resolve complex technical issues, and measure business impact in a regulated healthcare environment.