Top Tech Jobs & Startup Jobs in Denver & Boulder, CO

Provide day-to-day corporate and commercial legal support, including drafting, reviewing, and negotiating contracts. Manage cross-border matters involving the US, UK, and EU; independently handle routine legal issues; build legal processes; and coordinate external counsel for complex or jurisdiction-specific matters. Provide practical, commercially minded advice to the business.

Marketing interns will join Boulder Weekly’s Street Team, attend events, set up booths, distribute marketing materials, answer questions about the newspaper, create spec ads, and support grassroots and social media marketing. The role involves promoting Boulder Weekly positively, engaging with readers, and working 5–15 hours weekly, including some weekends. Reliable transportation, strong people skills, initiative, and the ability to stand for extended periods are required. This is an unpaid internship.

Own end-to-end launches and product upgrades across global markets. Coordinate Product Development, suppliers, Supply Chain, Ecommerce, Marketing, Sales, Compliance, and country teams to achieve launch readiness. Manage milestones, dependencies, risks, quality gates, documentation, inventory, Shopify setup, training, testing, and go/no-go decisions. Improve launch processes through retrospectives, risk tracking, SKU transitions, and installation manual quality improvements.

Supports the revenue team through Salesforce and Apollo data hygiene, CRM administration, reporting, AI-assisted workflow development, commission processes, performance reviews, and sales enablement. The intern will clean and manage records, research and automate repetitive tasks using AI tools, prepare confidential documents, verify numbers, and help train the revenue team on sales tools and processes.

Own and scale a TikTok creator community on Discord as a revenue channel. Responsibilities include creator recruiting, tiering, incentives, retention, training, funnel reporting, ROI analysis, people management, cross-functional coordination, escalations, automation, attribution, payment workflows, and playbook development. The role manages creator performance across GMV, content volume, conversion, and program economics while preparing operations for significant scale.

Build and deploy production machine-learning systems within client environments, covering data discovery, modeling, validation, deployment, scheduling, monitoring, and retraining. Develop forecasting and detection models for imperfect time-series data, establish honest evaluation and KPI frameworks, and ship usable APIs or interfaces. Work directly with client IT and data teams through discovery, demos, and feedback cycles. The role also involves data engineering, software development, basic cloud and DevOps work, and advising clients when ML is not appropriate.

Provides executive and operational support to the founders, managing calendars, inboxes, travel, leadership meetings, action items, hiring coordination, candidate pipelines, finance coordination, market research, marketing support, and ad-hoc projects. The role begins with administrative execution and expands into cross-functional project management, process design, and strategic initiative support. It requires high autonomy, discretion, sound judgment, strong communication, ownership, and the ability to organize a fast-paced startup environment.

Lead the design, development, deployment, and governance of advanced analytics, machine learning, and AI solutions using large healthcare datasets. Responsibilities include data preparation, statistical and predictive modeling, model monitoring, explainability, visualization, stakeholder communication, and translating findings into clinical and operational improvements. The role also mentors data professionals, advises leaders, manages initiative priorities and risks, and promotes responsible AI and Agile practices.

Lead and deliver Workday implementations with a focus on integrations. Design, build, test, and deploy Workday Studio integrations using Core Connectors, PECI, EIBs, and XSLT. Collaborate with business and technical stakeholders and own end-to-end integration lifecycle from requirements through production deployment.

Develops and deploys machine learning systems for high-stakes decisions in pricing, claims, underwriting, and predictive health. Responsibilities span problem framing, quantitative research, experimentation, causal inference, predictive modeling, multimodal and foundation model development, agent systems, production deployment, and ongoing iteration. The role requires strong mathematical and statistical foundations, Python fluency, and expertise in machine learning, statistics, econometrics, or causal inference.