Top Natural Language Processing Jobs in Denver & Boulder, CO

Partner with the SVP of Customer Success to improve executive effectiveness and organizational operating rigor. Responsibilities include calendar and meeting management, forecasting and business analytics, executive and board reporting, cross-functional initiative coordination, operating-rhythm management, action tracking, process improvement, and synthesizing data into insights, risks, decisions, and recommendations. The role combines executive support, business operations, project management, and analytical judgment.

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.

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.

Build and scale ML-optimized HPC infrastructure, manage Kubernetes-based GPU/TPU superclusters, optimize for AI/ML training, and mentor teams while innovating in ML infrastructure.

Provide high-level executive and personal support to the CEO, managing complex calendars, inboxes, meetings, travel, board and investor logistics, confidential documentation, follow-ups, and special projects. Serve as a trusted liaison with internal and external stakeholders while proactively resolving administrative challenges. The role requires flexibility outside regular hours, strong discretion, excellent organization, and fluency in Hebrew and English.

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.