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

Designs and leads end-to-end AI/ML solutions for consulting clients, including architecture, data pipelines, model deployment, monitoring, governance, and responsible AI practices. Advises stakeholders on AI strategy, conducts workshops, oversees delivery, supports presales activities, and develops reusable AI offerings. Collaborates with data scientists and engineers across cloud platforms while driving technical leadership, client relationships, and business outcomes.

Lead Machine Learning Engineer at CapTech will design data-driven solutions, implement machine learning systems, and provide technical leadership. Responsibilities include collaborating with clients and teams, analyzing large datasets, and managing ML practices.

Machine Learning Engineers design and implement data-driven solutions, build scalable ML systems, and collaborate with cross-functional teams at CapTech.

Design, build, and maintain cloud data pipelines and data products across AWS, Azure, or GCP. Advise clients on cloud data architecture, implement production database and ETL/streaming solutions, collaborate with stakeholders, and evaluate architectural tradeoffs to meet business needs.

Lead data strategy and delivery for clients by assessing architectures, defining data management and governance, recommending technologies, and mentoring teams. Translate business needs into actionable roadmaps, scope consulting engagements, and guide implementation of integrations, real-time streaming, NoSQL, and cloud data platforms.

Design and recommend end-to-end data architectures, assess data management technologies, improve data integration/quality, guide modernization (cloud, streaming, NoSQL, warehousing), mentor staff, collaborate with stakeholders, and support business development to deliver data-driven solutions.

Design, implement, and maintain cloud-based data pipelines and platforms. Advise clients on best practices, integrate disparate data sources, optimize data warehousing/lake solutions, mentor engineers, and ensure scalable, maintainable data architectures across cloud environments.