Top AI & Machine Learning Jobs in CO

Develops research methods for context discovery, retrieval, multimodal representation, reasoning, tool calling, metadata management, and trustworthy AI data pipelines. Builds and evaluates foundation models across language, vision, time series, and scientific applications. The role combines applied research with hands-on engineering, including MLOps, agentic AI, knowledge-infused learning, pipeline optimization, and collaboration with software teams and external partners.

Lead customer-facing architecture for AI data platforms and AI Factory environments. Design data-centric solutions for RAG, inference, and training workflows; size GPU and storage environments; optimize data movement, retrieval, latency, throughput, cost, and reliability. Partner with customers, sales, and Product Management to qualify opportunities, influence product roadmaps, create reference architectures, and develop scalable go-to-market solutions.

Own product areas within HPC/AI system management and orchestration software: define requirements, prioritize features, create PRDs and user stories, collaborate with architects and engineering, engage customers, support releases and go-to-market, and monitor product performance to drive improvements.

Lead the architecture and technical direction of HPE’s LLM inference runtime and Kubernetes orchestration platform. Own engine integration, continuous batching, KV cache management, quantization, distributed inference, GPU scheduling, autoscaling, and performance optimization. Evaluate emerging inference technologies, mentor engineers, lead architecture reviews, and communicate technical strategy to executives. The role targets low latency, high throughput, and efficient GPU utilization across enterprise, air-gapped, and sovereign environments.

Leads the architecture, strategy, and implementation of applied and agentic AI capabilities for HPE private and hybrid cloud offerings. Designs production-grade AI architectures, multi-agent systems, LLMOps, AI security, governance, observability, and knowledge layers. Builds reusable AI components, optimizes large-scale AI systems, guides technology selection, and converts proofs of concept into reliable services. Influences customers and internal teams through technical workshops, reference architectures, publications, and presentations while mentoring engineers and architects.

Supports data science projects by preparing and validating datasets, maintaining metadata, conducting exploratory analysis, developing and validating analytical models, researching data science solutions, and visualizing model insights. Works with team members to provide analysis and recommendations for business decision-making. The role requires a bachelor’s degree in data science, statistics, operations research, computer science, or an equivalent field, and typically targets candidates with 0–2 years of experience.

Design and scale AI-powered sales enablement experiences: architecture for generative AI, RAG, AI agents, content discovery, guided selling, coaching automation, governance, pilots, integrations with enablement/CRM/LMS systems, and measure adoption and business impact.