Top AI & Machine Learning Jobs

Design and deploy production-grade ML models and GenAI/LLM solutions to improve customer segmentation, churn prediction, LTV estimation, and automate enterprise workflows. Build cloud-native data science pipelines, measure impact via experiments, create executive dashboards, and mentor peers on MLOps and data storytelling.

Leads AI engineering teams building and scaling production-grade agentic AI applications, multi-agent systems, LLM orchestration, and intelligent workflows. Oversees Databricks on AWS platform operations, architecture, security, and optimization. Establishes engineering standards for Python development, testing, CI/CD, and DevOps/DataOps, while partnering with Product teams on execution. Manages engineering leaders and staff, drives hiring and mentorship, and shapes the organization’s AI technical direction.

Build and scale AI infrastructure through Python automation, AWS serverless architectures, EKS containerized workloads, Terraform infrastructure as code, and monitoring. Develop orchestration pipelines for model training and inference, manage large datasets and production availability, reduce recovery times, collaborate with QA and Product, and mentor engineers while maintaining code quality and operational performance.

Lead design and delivery of AI-powered order orchestration platforms. Define architecture, drive roadmap, implement scalable microservices and real-time streaming pipelines, productionize AI models, enforce CI/CD and engineering best practices, resolve performance bottlenecks, and mentor engineering teams.

Embed AI solutions across legal and corporate affairs to remove workflow bottlenecks, build rapid prototypes for contract analysis and regulatory tracking, enforce data governance, and deliver executive reporting and KPIs to drive legal operations efficiency and risk mitigation.

Partner with HR leaders to define AI strategies, build KPIs, and deliver ROI. Design and deploy generative AI prototypes (e.g., Google AI Studio), integrate across ServiceNow, Jira, and HRIS, enforce data governance and compliance, automate executive reporting and workforce analytics, and translate technical solutions for non-technical HR stakeholders to accelerate AI adoption.

Develops and operationalizes AI and data governance policies, standards, procedures, checklists, decision trees, and reporting templates. Translates frameworks including NIST AI RMF, the EU AI Act, and Colorado ADMTA into practical workflows. Partners with engineering, data science, product, governance, risk, and business teams to test standards, define metadata and logging requirements, and enable cross-functional execution through version-controlled policy frameworks.

Lead automation and measurement of the AI Governance program by building self-service dashboards, tracking Time-to-Approval and throughput metrics, analyzing trends to remove bottlenecks, producing C-suite evidence packs, and recommending process improvements to increase governance maturity and delivery velocity.

Partner with business leaders to define AI strategy, set KPIs, and deliver executive reporting; prototype AI solutions (e.g., Google AI Studio); remove operational obstacles across ServiceNow, Jira, and automated workflows; enforce data governance and privacy to enable enterprise AI adoption and measurable ROI.

Lead scaling of AI initiatives across Direct Sales by translating call and performance data into prioritized AI roadmaps, driving deployment, managing cross-functional stakeholders, mitigating risks, and reporting ROI-focused insights to senior leadership.