Top AI & Machine Learning Jobs

Build and own AI team systems spanning data ingestion, labeling, training and evaluation infrastructure, model deployment, perception integration, and customer-facing applications and APIs. Drive high-impact technical projects, make hands-on architectural decisions, mentor engineers, and support a broad AI software stack. The role is approximately 70% backend and 30% frontend, with focus areas including ML Ops, data pipelines, or computer vision.

Own evaluation systems and model-quality improvements for a generative content platform producing AI-generated ecommerce content. Build datasets, rubrics, automated judges, quality gates, and labeled training data from brand feedback. Quantify qualitative improvements, establish approval thresholds, and drive fine-tuning or retrieval experiments into production. The role requires strong software and system design skills, production service ownership, formal machine learning or statistics training, and experience measuring correctness in non-deterministic systems.

Develops production-ready AI, data automation, integration, and workflow solutions for engineering processes in an aerospace and defense environment. Responsibilities include programming, API and database integration, engineering toolchain integration, CI/CD, testing, documentation, workflow analysis, roadmap development, training, and user support. The role collaborates with systems engineers and customer teams and may deploy tools in classified environments.

Lead design and delivery of high-priority AI initiatives across product and platform boundaries. Rapidly prototype and launch AI features, unblock teams, mentor engineers, and shape production-grade LLM systems (retrieval, evals, prompting, orchestration). Collaborate with product, design, and domain experts to turn customer needs into shipped product.

Design, build, deploy, and optimize AI-powered agents with Salesforce Agentforce, LLMs, RAG, and agentic workflows. Integrate Salesforce with enterprise systems, configure Salesforce clouds and Einstein AI, and translate customer requirements into secure production solutions. Lead workshops, demonstrations, and technical discussions while contributing to DevOps, CI/CD, governance, documentation, and agile delivery. Serve as a client-facing technical partner connecting business needs with AI-enabled implementation.

Develop and evaluate perception algorithms for autonomous vehicles, including road-user detection, scene understanding, and road-structure estimation. Train and optimize machine learning models, validate performance in simulation and real-world driving environments, analyze failure modes, and build research software in Python and C++. Collaborate with autonomous systems teams, present technical findings, and contribute to publications, patents, and research initiatives.

Build production-grade generative AI solutions that improve advisor productivity and client engagement. Responsibilities include developing LLM-powered applications, agent workflows, RAG and semantic search systems, enterprise knowledge platforms, decision-support tools, and workflow automation. The role also requires full-stack development, cloud deployment, platform engineering, DevOps, scalable architecture, security, and reliability practices, while leading initiatives across engineering, data, product, and business teams.

Lead Vizient’s enterprise AI adoption and enablement strategy by creating scalable training, governance, engagement, solutioning, and measurement frameworks. Partner with technology, product, learning, communications, and change management leaders to align AI initiatives with business priorities, drive adoption, measure value, and influence senior stakeholders. The role also includes executive communications, strategic recommendations, and leadership of up to two direct reports.

Lead SRE ownership of ML platform SLOs and operational health for Ray on EKS and Databricks on EC2. Maintain observability with CloudWatch/Datadog, tune autoscaling and GPU scheduling, manage Databricks workspaces and IAM, optimize cost/capacity, codify infrastructure with Terraform and CI/CD, lead incident response and postmortems, perform security/OS maintenance, and participate in on-call rotation.

Leads Ivy Tech’s enterprise data, analytics, and AI strategy. The role oversees governance, data quality, privacy, responsible AI, reporting, dashboards, advanced analytics, and AI-enabled insights. It advises executives, aligns initiatives with institutional priorities, evaluates emerging technologies, and leads data, institutional research, and business intelligence teams. The AVP also partners with technology leaders on scalable data platforms and prepares executive and Board-level recommendations.