Top Natural Language Processing Jobs in Denver & Boulder, CO

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.

Own partner-network relationships after agreement signing, managing onboarding, contractual commitments, co-marketing, advisor adoption, and network penetration. Drive net-new bookings, expansions, trials, conversions, webinars, demos, and enablement activities. Track activation and pipeline metrics in Salesforce, coordinate with strategic partnerships, marketing, sales, account management, RevOps, and product teams, and forecast bookings across multiple financial-advisor networks.

Designs and maintains automated test frameworks and exploratory suites for products, APIs, SDKs, AI models, and data platforms. Develops functional, integration, end-to-end, regression, API, browser, load, and reliability tests; creates datasets, evaluation pipelines, dashboards, and CI/CD release gates. Partners across Engineering, Research, Product, Data, and Infrastructure to validate model behavior, data quality, performance, and production readiness. Documents reproducible defects, supports triage, and communicates risks.

Leads Pfizer’s global customs governance and compliance framework, including Belgian Authorized Economic Operator status, internal controls, customs valuation reporting, audits, continuous improvement, and stakeholder partnerships. Provides technical expertise in customs law and operations while implementing standardized, automated workflows aligned with GDP, GMP, and local regulations. Oversees talent development, performance standards, budgeting, and strategic customs initiatives across global operations.

Develop product launch narratives and messaging that connect with customers and prospects. Create demos, case studies, webinars, campaigns, web content, and customer stories. Partner cross-functionally with product, sales, and customer success to ensure consistent positioning. Conduct customer and prospect research, identify market trends, and use data-driven insights to strengthen product marketing strategy.

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.

Lead an established RevOps and Enablement team to sharpen analytics, harden systems and data architecture, and scale AI-first workflows across Sales, Marketing, and CX. Own revenue tech stack, forecasting, GTM reporting, process optimization, and enablement programs while partnering with executive leadership to drive measurable revenue outcomes.

Owns the operational health, governance, and integrity of customer and prospect data across Salesforce, Marketo, Demandbase, and related GTM systems. Responsibilities include data stewardship, deduplication, enrichment, lifecycle management, integration monitoring, synchronization troubleshooting, segmentation support, data-quality dashboards, process documentation, automation improvements, and audit support. Partners cross-functionally with Revenue Operations, Marketing, Sales, Customer Success, Analytics, and Data Engineering to enable reliable reporting, automation, and AI workflows.

Design and manage global early-career and internship programs for technical talent. Responsibilities include university partnerships, campus recruiting, employer branding, onboarding, mentoring, intern engagement, performance reviews, retention, program metrics, feedback analysis, budgets, logistics, and continuous program improvement. The role collaborates across global People and stakeholder teams to scale inclusive early-career talent initiatives.

Source and engage high-quality business talent across sales, finance, revenue, marketing, communications, and operations. Build talent pipelines, partner with hiring managers and talent partners, manage recruiting funnels in the ATS, monitor sourcing analytics, maintain market intelligence, develop proactive sourcing strategies, cultivate professional networks, and lead high-impact talent projects while supporting inclusive hiring.

Develop and execute employer branding and recruitment marketing strategies to attract frontier AI talent globally. Manage multi-channel campaigns, create career content, optimize the career site, track recruitment metrics, monitor competitors, and partner with Marketing, Communications, Research, and hiring teams to deliver targeted campaigns and consistent employer messaging.

Design and lead scalable data engineering solutions across Databricks and Microsoft Azure. Define enterprise data modeling standards, architect pipelines and integrations, establish engineering best practices, troubleshoot complex platform issues, and guide modernization and cloud migration initiatives. Provide technical leadership and mentorship while ensuring data platforms meet security, quality, governance, reliability, performance, and maintainability standards.

Design, develop, and maintain scalable data pipelines and models in Databricks and Microsoft Azure. Perform data ingestion, transformation, integration, migration, and modernization across enterprise data sources. Monitor and optimize pipeline performance, reliability, and data quality. Translate business requirements into technical solutions, collaborate with architects and engineers, follow security and governance standards, participate in code reviews, and document data platforms and processes.

Design, build, and deploy production-grade AI applications, agents, retrieval systems, integrations, and workflows for enterprise customers. Lead technical discovery, architecture workshops, prototyping, troubleshooting, deployments, and go-live support. Translate customer needs into scalable solutions and reusable engineering patterns, while providing product feedback that informs roadmaps. Partner with Product, Sales Engineering, Customer Success, and Engineering teams, and mentor customer-facing engineers. Travel to customer sites as needed.