Top Natural Language Processing Jobs in Denver & Boulder, CO

Own technical go-to-market enablement for pre-sales and post-sales teams. Build onboarding, ramp programs, technical frameworks, playbooks, certifications, launch readiness, and scalable guidance from subject-matter expertise. Partner with Product, Applied Engineering, Customer Success, Sales, and PMM to improve technical discovery, evaluations, architecture guidance, handoffs, escalations, and customer readiness. Use AI, scripts, agents, and workflows to eliminate recurring work and scale enablement.

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.

Develops and commercializes partner-built solutions across the Superhuman Suite. Responsibilities include shaping joint value propositions, creating pitch and demo assets, enabling alliance managers and partners, packaging repeatable solutions, coordinating launches, supporting partner growth, and tracking post-launch performance. The role works across Alliance Programs, Partner Marketing, Technical Alliances, Product, and solution architecture, with approximately 25% international travel.

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 end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

Lead AlphaSense’s global compensation function, including compensation strategy, job structures, base pay, incentives, equity, executive compensation, and annual review cycles. Partner with Finance, Legal, People Business Partners, and leaders on market competitiveness, pay equity, compliance, offers, promotions, and governance. Manage Workday compensation administration, support IPO and Compensation Committee readiness, and build and develop a global compensation team.

Translate, copy-edit, and post-edit machine-translated content from English into Brazilian Portuguese for marketing, UI, product, support, informational, and legal materials. Use client-specific CAT tools, meet weekly volume and deadlines, maintain high linguistic quality, communicate reliably, and incorporate feedback and revisions in a remote freelance localization environment.

Lead the vision, roadmap, development, and delivery of cybersecurity threat intelligence products and the Global Intel Graph portfolio. Manage large-scale intelligence data, standardize cybersecurity entities, define integrations, and partner with engineering and domain experts. Validate SME data and AI-generated intelligence through labeling, accuracy checks, edge-case testing, and customer feedback. Lead cross-functional teams, communicate strategy to executives, and build scalable capabilities that improve threat detection and response.

Develop and maintain enterprise and SaaS backend applications using Java and Spring Boot. Design RESTful APIs, manage authentication and authorization, build database models and queries, conduct code reviews, improve application performance and security, and collaborate with technical and business stakeholders. The role also involves testing, deployment, documentation, and maintaining cloud-based applications using AWS and Docker.