Top Natural Language Processing Jobs in Denver & Boulder, CO

Lead the developer experience roadmap and own multi-language SDKs and the code-generation pipeline. Design CI, release automation, observability, and tooling (CLI, starter repos). Improve cross-language parity, docs, and developer onboarding; remove systemic friction and represent DX to Product, Engineering, and Partnerships.

Intern will own and deliver a scoped engineering project on Deepgram's voice platform (ASR/TTS/LLM/API/SDK), ship reviewed code to staging/production, use AI in development workflows, improve a component measurably, and present results with documentation.

Lead optimization and experimentation for Pfizer's HCP web properties (primarily PfizerPro). Develop experimentation roadmaps, run A/B and multivariate tests, analyze web and business metrics, partner with UX, analytics, and strategy to translate insights into product and design improvements, and adopt AI-enabled tools to scale personalization and accelerate test velocity while maintaining rigorous measurement.

Lead demand generation programs for Superhuman Mail, collaborating with Sales and other teams to drive marketing-sourced pipeline growth through integrated campaigns, optimization, and performance analysis.

Own and grow Hebbia's Middle East enterprise sales: prospect, run demos, negotiate and close large deals with sovereign wealth funds, asset managers, banks and PE/VC; build regional pipeline, represent the company at events, partner on technical evaluations, inform product and GTM strategy, and hire a regional team.

Deliver tailored live training sessions and workshops for clients on using EliseAI products effectively, while collecting feedback and improving internal programs.

The Enterprise Account Executive will drive sales by managing the sales process, generating new business, engaging with prospects, and achieving revenue targets.

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.

As a Solutions Architect, you will design and optimize customer solutions for deploying LiteLLM, collaborating with customers and engineering teams to ensure successful implementations.

Own the full enterprise sales cycle for developer-focused SaaS, drive revenue to hit targets, gather customer feedback for product, build repeatable scalable processes, and help hire and define the future sales team.

Work across frontend and backend to design, build, and ship annotation and review features; implement ingestion, storage, user management, and annotation pipelines; integrate model inference into workflows; optimize performance for large images/videos; design APIs and collaborate with product, operations, and annotators.

Label and outline plants in agricultural images using an online tool, tag crop and weed types per guidelines, maintain high accuracy across many images. Remote, flexible internship (3 months) with a monthly stipend and completion certificate. No coding or prior labeling experience required; video tutorials provided.

Seeking a technical co-founder to architect and lead development of an AI-powered data-labeling SaaS. Drive platform and ML engineering, leverage foundational models for AI-assisted labeling, build MVP/demo, and shape product and team. This is an equity-first, no-salary founding role at an early-stage, bootstrapped startup.

Lead technical pre-sales engagements to drive product fit and revenue: demo, prototype, run POCs, respond to RFPs, qualify KPIs, build custom search solutions, and relay customer feedback to Product and Engineering while ensuring smooth handoffs to post-sales teams.

Drive technical pre-sales by partnering with Account Executives to perform technical discovery, demos, POCs, and RFP responses. Advocate customer needs to Product and Engineering, create technical content, enable teams, and support smooth handoffs to post-sales for successful onboarding and adoption of Algolia solutions.

The Solutions Architect at Algolia will guide enterprise customers in deploying AI search solutions, provide technical advice, and enhance product usage. Responsibilities include consulting on architecture, troubleshooting issues, conducting training, and collaborating with internal teams to improve customer success and product development.