Machine Learning Jobs in Fort Collins, CO

Build production AI/ML software for supercomputers and AI infrastructure, including anomaly detection, forecasting, root cause analysis, automation, and operational intelligence. Develop services with Go, Python, and React; integrate machine learning models, LLM workflows, agentic systems, and analytics. Own the lifecycle from data engineering and model development through deployment, monitoring, and improvement while collaborating with engineering, architecture, product, and customers.

Build production AI and machine learning software for large-scale computing and AI infrastructure. Responsibilities include developing anomaly detection, forecasting, root cause analysis, LLM workflows, agentic systems, and operational analytics using Go, Python, and React. The role spans data engineering, model development, evaluation, deployment, monitoring, and continuous improvement while collaborating with engineering, architecture, product, and customer teams.

Develop AI data infrastructure, metadata and lineage systems, foundation models, agentic AI platforms, and knowledge-infused learning capabilities. Build and evaluate NLP, LLM, time-series, diffusion, and computer vision systems while improving reproducibility, governance, reasoning, scalability, and trustworthy AI outcomes. Partner with software teams and external collaborators to translate innovative research into production implementations.

Develop and lead an internationally recognized research program in electric propulsion and plasma-based systems. Conduct experiments, publish research, secure patents and external funding, manage sponsored projects, collaborate with industry and government partners, and supervise high-vacuum testing and laboratory operations. Mentor undergraduate and graduate students, advise PhD and master’s research, teach effectively, and provide departmental, university, professional, and community service.

Assistant Professor will establish an externally funded research program investigating genotype-to-phenotype relationships and genotype-environment interactions. Responsibilities include publishing and presenting research, teaching undergraduate and graduate courses, mentoring trainees, advising students, and contributing departmental and university service. The role requires a biology-related Ph.D., at least one year of postdoctoral experience, and publications in genotype-to-phenotype research.

Develops research methods for context discovery, retrieval, multimodal representation, reasoning, tool calling, metadata management, and trustworthy AI data pipelines. Builds and evaluates foundation models across language, vision, time series, and scientific applications. The role combines applied research with hands-on engineering, including MLOps, agentic AI, knowledge-infused learning, pipeline optimization, and collaboration with software teams and external partners.

Supports microgrid controls engineering through operational data analysis, dashboards, anomaly detection, predictive insights, and system optimization. Conducts MIL and HIL testing of control strategies, develops AI and automation tools, supports verification and validation, and contributes to engineering standards and emerging power systems research.

Leads a technical AI/ML engineering team while remaining hands-on in designing, developing, testing, and deploying software prototypes. Owns architecture, technical direction, planning, execution, risk management, customer communication, and delivery across R&D and funded projects. Conducts design and code reviews, mentors engineers, supports proposals, and translates mission needs into practical solutions for national security applications including air, space, and missile defense.

The role involves developing software tools for semiconductor compilers, creating an ecosystem for efficient IP generation, and requires knowledge in circuit design and programming.

The Physical Design Engineer will lead efforts in solving physical design challenges, improve RTL-to-GDS methodologies, and integrate AI/ML solutions into CAD flows, focusing on performance and runtime improvements.