Top Natural Language Processing Jobs in Denver & Boulder, CO

Owns product operations across roadmap coordination, new product introduction, launch readiness, partner deliverables, financial and revenue analysis, metrics, executive reporting, and cross-functional planning. The role maintains product commitments, drives accountability, leads launch gates, models business impact, coordinates sales and marketing readiness, and supports leadership decision-making through business reviews, planning, and board materials.

Own SEO and AEO initiatives across multiple domains, driving organic visibility, qualified traffic, conversions, and AI-search presence. Conduct keyword, competitor, technical, and performance analysis; recommend content, metadata, site structure, and structured-data improvements; partner with content, marketing, web, engineering, and analytics teams; support launches and offsite authority efforts; measure search visibility, citations, mentions, and business impact; and communicate actionable findings to stakeholders.

Provide legal counsel across product lifecycle for AI agents and SaaS products, triage and resolve legal issues, advise Product/Design/Engineering/Marketing, manage IP, monitor AI/privacy regulations, build scalable compliance processes, and deliver training.

Own end-to-end localization operations for enterprise clients, serving as the primary operational contact and trusted advisor. Coordinate stakeholders and cross-functional teams, manage localization workflows and configurations across TMS and project tools, resolve client and internal issues, and improve processes through documentation, automation, and AI-enabled solutions. The role requires localization or translation project management experience, client communication skills, familiarity with localization formats and CAT/TMS tools, and strong organizational abilities.

Work through a backlog of unconverted marketing leads using phone, AI-assisted LinkedIn prospecting, and persistent outreach. Qualify prospect interest, arrange well-prepared handoffs to Account Executives, maintain accurate CRM records, and share prospect feedback with Sales and Marketing. The role primarily targets financial advisors and wealth management professionals and focuses on increasing marketing-lead conversion.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

Own product areas from customer discovery through launch and measurable outcomes. Partner closely with legal professionals and enterprise stakeholders to understand workflows, define requirements, prioritize roadmaps, and validate prototypes. Collaborate with Engineering, ML, Design, Sales, and Customer Success to build scalable AI-powered legal products, incorporating security, permissions, integrations, governance, and enterprise rollout needs. Use customer evidence and adoption data to distinguish platform opportunities from one-off requests and shape product strategy.

Perform high-volume digital content curation and metadata validation for written and audio content. Follow SOPs, checklists, and client guidelines; correct straightforward issues, document defects in internal tools, escalate complex problems, manage assigned queues to SLA targets, and maintain accuracy and confidentiality while incorporating feedback through training and calibration.

Evaluates and integrates financial datasets and content for an AI-powered market intelligence platform. Leads vendor due diligence, data trials, proofs of concept, quality and coverage assessments, business cases, licensing strategies, competitive research, and content roadmap development. Partners with engineers, content leaders, partnership managers, and vendors to identify high-impact investment research data and AI workflow opportunities.

Design, build, deploy, and operationalize Palantir Foundry solutions for defense and security customers. Develop data pipelines, ontology models, operator applications, integrations, and custom widgets using real-time intelligence. Debug infrastructure, networking, and application layers across cloud, hybrid, restricted, disconnected, and on-premises environments. Partner with customer stakeholders, advise technical teams, and own solutions end to end. Travel to secure customer sites and operations centers approximately 25–75% of the time.

Own full-cycle enterprise sales from prospecting through close, targeting CISOs, CIOs, General Counsels, and other stakeholders. Build strategic account plans, generate outbound pipeline, demonstrate forensic watermarking technology, navigate complex organizations, exceed revenue quotas, and provide market feedback to product teams. As an early go-to-market hire, contribute to developing the sales playbook in a fast-paced startup environment.