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

Design and develop multimodal foundation-model algorithms and architectures, run large-scale experiments, improve training and deployment efficiency, build datasets and pipelines, perform rigorous evaluation and ablation studies, and collaborate with infrastructure, data, and product teams to responsibly advance AI systems.

Design, build, benchmark, and operate large-scale reinforcement learning and pretraining systems on NVIDIA and AMD GPU clusters. Optimize distributed, parallel software for training models, gather compute-roadmap data, and collaborate to deliver production-grade conversational and generative AI features.

Drive product strategy and KPIs for backend networking of ultra-large AI supercomputers. Identify failure points, lead remediations and roadmap changes, and coordinate cross-functional teams including customers, datacenter operators, vendors, and product groups to maximize uptime and AI workload throughput.

Design, develop, and optimize high-performance, low-latency networking infrastructure for large-scale AI training on Azure. Benchmark, debug, and improve scalability, reliability, observability; author design documents; act as DRI and participate in on-call operations.

Design and implement next-generation networking infrastructure for large-scale AI training on Azure. Lead architecture, write secure high-performance code, create test strategies, perform and coach code reviews, integrate AI tools in the SDLC, and collaborate cross-team to ensure scalability, reliability, observability, and security for distributed HPC/AI systems.

Design, implement, and optimize low-level software for Azure HPC/AI VMs. Diagnose HW/SW integration and performance issues, drive cross-team solutions, maintain service stability, and develop operational playbooks.

Design, build, and optimize high-performance, low-latency networking infrastructure for large-scale AI training on Azure. Benchmark and improve scalability, reliability, and observability; debug complex network issues; author design documents; act as DRI and participate in on-call operations to restore and maintain service availability.

Design and build monitoring, telemetry, and data pipelines to operate flagship supercomputers at scale. Diagnose and troubleshoot GPU hardware, networking, datacenter and software stack issues, implement systemic mitigations, improve observability, and drive reliability and performance improvements through incident reviews and tooling.

Design, curate, and evaluate large-scale text datasets for LLM pretraining. Build scalable ingestion, preprocessing, filtering, annotation pipelines; run data ablations and analyses; create auditing, visualization, and versioning tools; and collaborate with Safety, Ethics, and Governance to ensure dataset quality, privacy, and responsible AI alignment.

Lead end-to-end data science and AI engagements: design, develop, deploy and evaluate models, mentor teams, partner with stakeholders, drive adoption, and apply Responsible AI to deliver measurable business impact.