Top Natural Language Processing Jobs in Denver & Boulder, CO

Own Deepgram’s AI applications product line, including strategy, roadmap, customer definition, acquisition, activation, retention, monetization, and profitability. Lead zero-to-one product development, represent the product with customers and partners, and coordinate research, engineering, design, and marketing. Prototype and validate ideas through real usage and measurement while communicating decisions to executives. The role requires shipped, paid consumer or prosumer products, deep AI application experience, technical depth, design judgment, and strong product leadership.

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.

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 and evolve Cohere’s Waypoint design system across Figma and production code. Responsibilities include maintaining component libraries, design tokens, documentation, sync tooling, and component packages; partnering with designers and engineers; making architecture and versioning decisions; and exploring how AI models can consume design systems. The role also supports accessibility, multi-platform systems, and design-to-code workflows.

Reviews, validates, and curates Hindi written and audio content according to SOPs, checklists, and client guidelines. The role checks content and metadata, applies approved corrections, documents defects in internal tools, escalates complex issues, manages queues to meet throughput and SLA targets, and follows security requirements. It also involves repetitive high-volume work, team meetings, calibration sessions, training, and incorporating feedback to improve accuracy.

Lead and develop Sales Directors and Account Executive teams within the High Growth corporate sales organization. Own go-to-market strategy for new logo acquisition and expansion, drive forecasting and pipeline management, support complex enterprise deals, engage executive clients, and collaborate cross-functionally with product, marketing, sales operations, customer success, and talent acquisition to accelerate revenue growth and build a high-performance culture.

You will execute and improve insurance workflows, analyze operational efficiency, collaborate with product teams, and support onboarding and documentation efforts.

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.