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

Review, label, and QA datasets for AI/ML training; maintain trackers, databases, and dashboards; follow annotation guidelines and SOPs; prepare and clean data; document processes; collaborate to resolve data queries while ensuring confidentiality and timely delivery.

Lead marketing operations by managing intake, workflow, resource planning, and cross-functional coordination. Build dashboards and reporting, optimize project delivery processes and marketing technology, and identify/resolve risks to ensure campaigns launch on time and meet quality standards.

Provide dedicated remote IT support managing high ticket volumes and SLAs; troubleshoot Mac and Windows systems; provision devices and accounts; support onboarding/offboarding; assist with MDM, network, and hardware rollouts; maintain documentation and compliance (SOC2/HIPAA); configure automations; and mentor junior staff.

Lead and scale Roo's revenue organization across both sides of the veterinary marketplace. Build GTM strategy, territory coverage, hiring and coaching processes, forecasting and QA loops, CRM/tooling architecture, cross-functional alignment, and performance-driven enablement to drive activation, retention, and revenue growth.

Own technical success for strategic accounts building AI and agentic platforms on Solo.io products. Provide architecture guidance, hands-on troubleshooting, adoption driving, workshops, and cross-team advocacy to ensure reliable, secure production deployments of cloud-native AI workloads.

Build and maintain executive and project-level dashboards, standardize and cleanse source data, define reporting conventions and KPIs, perform data quality checks, coordinate with stakeholders, and apply AI/LLM tools to improve reporting workflows and efficiency.

The Machine Learning Engineer will build data-intensive products, deploy ML models, analyze datasets, and collaborate with product teams to enhance Nextdoor's platform.

Partner with customers to deploy collaborative robots: perform onsite hardware/software testing, troubleshoot and repair, conduct readiness assessments, document procedures, replace parts/retrofits, and drive project communication to ensure successful long-term adoption.

Lead end-to-end delivery of enterprise AI projects for federal customers, shaping use cases, managing cross-functional teams, ensuring timely scope/budget compliance, driving value realization, identifying expansion opportunities, and refining scalable delivery frameworks while interfacing with C‑suite and working on National Security problems.

Develop, validate, and improve machine learning models (regression, classification, forecasting, optimization). Prepare data, perform feature engineering, train and evaluate models, and support deployment with Data/ML Engineering. Communicate results, document methods, and collaborate on experiments and cross-functional initiatives.