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Machine Learning Computational Chemistry Jobs in Colorado

AI/ML Engineer

Aurora, CO · On-site

$110 - $160/hr

... Machine Learning, Data Science, Robotics, Electrical Engineering, Mathematics, Statistics, Computational Linguistics, Software Engineering, etc. ALTERNATE EXPERIENCE General comment on degrees: Most ...

... Machine Learning, Data Science, Robotics, Electrical Engineering, Mathematics, Statistics, Computational Linguistics, Software Engineering, etc. ALTERNATE EXPERIENCE General comment on degrees: Most ...

Dam Computational Modeling Technical Lead

Denver, CO · On-site

$105K - $139K/yr

Experience with machine learning. * SE a plus * PhD a plus Future Serve as HDR's national technical ... The role bridges high-end computational mechanics, consulting practice needs, and owner-facing ...

Apply machine learning, data science, and computational biology techniques to investigate biological mechanisms and identify novel therapeutic targets. Support the design and implementation of ...

Leverage statistics and computational techniques in problem solving. * Be familiar with common NLP and machine learning techniques. * Research and use applicable models in creative problem solving.

Algorithm Developer

Fort Collins, CO · On-site

$100K - $190K/yr

We are looking for algorithm and software developers with experience and/or an educational background in: signal processing, machine learning, estimation theory, computer vision, computational ...

Showing results 41-60

Machine Learning Computational Chemistry information

See Colorado salary details

$23.1K

$107.8K

$199.1K

How much do machine learning computational chemistry jobs pay per year?

As of Aug 23, 2026, the average yearly pay for machine learning computational chemistry in Colorado is $107,754.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,483.00 and $145,436.00 per year, depending on experience, location, and employer.

What is machine learning computational chemistry?

Machine learning computational chemistry is a field that combines machine learning techniques with computational chemistry to accelerate the discovery and design of molecules and materials. By training algorithms on large datasets of chemical information, researchers can predict molecular properties, simulate chemical reactions, and optimize compounds more efficiently than traditional methods. This approach helps reduce the time and cost required for research in drug discovery, materials science, and related fields.

What are some common challenges faced by professionals working in machine learning computational chemistry roles?

One common challenge in Machine Learning Computational Chemistry roles is integrating large and often complex chemical datasets with appropriate machine learning models, which requires a solid understanding of both domains. Professionals may also encounter difficulties in ensuring that their models are both interpretable and generalizable to new data, as overfitting is a frequent issue. Additionally, collaboration with chemists and data scientists is essential, so clear communication across disciplines is key to success. Staying up to date with the latest developments in both computational chemistry and machine learning is crucial for ongoing professional growth.

What are the key skills and qualifications needed to thrive as a machine learning computational chemist, and why are they important?

To thrive as a Machine Learning Computational Chemist, you need a solid background in chemistry, mathematics, and computer science, typically supported by an advanced degree in computational chemistry, cheminformatics, or a related field. Proficiency with programming languages (such as Python), machine learning frameworks (like TensorFlow or PyTorch), and molecular modeling software is essential. Strong analytical thinking, problem-solving skills, and effective collaboration are key soft skills that help drive innovation and teamwork. These skills and qualifications are critical for developing accurate models, advancing research, and translating computational insights into real-world chemical solutions.

What is the difference between Machine Learning Computational Chemistry vs Computational Chemist?

AspectMachine Learning Computational ChemistryComputational Chemist
Required CredentialsAdvanced degrees in chemistry, computer science, or related fields; knowledge of machine learning and programmingDegree in chemistry, chemical engineering, or related fields; strong background in chemical theory and modeling
Work EnvironmentResearch labs, tech companies, academia; focus on algorithm development and data analysisLaboratories, research institutions, industry; focus on chemical modeling and simulation
Employer & Industry UsageTech firms, pharmaceutical companies, research institutions applying AI/ML techniquesPharmaceutical, chemical, and materials industries conducting chemical research and development

Machine Learning Computational Chemists specialize in applying machine learning algorithms to chemical data, enhancing predictive models and simulations. Computational Chemists focus on traditional chemical modeling and simulations using computational methods. Both roles require strong chemistry backgrounds, but Machine Learning Computational Chemists emphasize data science and AI skills, while Computational Chemists focus on chemical theory and modeling techniques.

What are popular job titles related to Machine Learning Computational Chemistry jobs in Colorado?

For Machine Learning Computational Chemistry jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Machine Learning Computational Chemistry jobs in Colorado look for?

The top searched job categories for Machine Learning Computational Chemistry jobs in Colorado are:

What cities in Colorado are hiring for Machine Learning Computational Chemistry jobs?

Cities in Colorado with the most Machine Learning Computational Chemistry job openings:

AI Data Foundation Research Engineer

Hewlett Packard Enterprise

Fort Collins, CO • Hybrid

$113K - $136K/yr

Full-time

Re-posted 5 days ago


Hewlett Packard Enterprise rating

8.4

Company rating: 8.4 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

36th of 159 rated electronics manufacturers


Job description

AI Data Foundation Research EngineerThis role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world.Our culture thrives onfinding new and better ways to accelerate what's next.We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs.We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you.Open up opportunities with HPE.

Job Description:

Successful candidate will develop new methods for context discovery, retrieval, filtering, prioritization, multi-modal data representation, advanced reasoning, tool calling, and reasoning trace validation in conversational, deep research, and agentic AI workflows. Successful candidate will also work on development of capture, management, search, enhancement and interpretation of meta-data and lineage for AI pipelines that enable reproducibility, reuse and optimization of pipelines; discovery, selection and usage of relevant high quality data for trustworthy AI outcomes across multiple AI applications; development, evaluation and testing of Foundation AI models for different modalities: Natural Language Processing - NLP, Large Language Models - LLM, Time Series Analysis, Computer Vision, AI for Science, etc., and augmentation of AI models with structured knowledge (i.e., knowledge infused learning). We are particularly interested in individuals with a background in computer systems, machine learning, deep learning, statistics, generative AI, data management, and big data pipelines, with good understanding of the current state of the art, major trends and opportunities, and a demonstrated track record in innovative research. The ideal candidate can thrive in an applied research environment, balancing significant technical contributions published externally in open source with the hands-on engineering skill to bring such contributions to practice in partnering with our internal software development teams and external partners.

Must-have Requirements
  • PhD in Computer Science or related fields with a focus on data engineering and data science, in particular Machine Learning, Deep Learning, and/or data management for AI, plus 3 years of relevant industry experience.
  • Research experience in Generative AI, Deep Learning and Machine Learning
  • Experience with advanced AI model architectures: LLMs, Time Series Foundation Models, Diffusion Models, etc.
  • Expertise with end-to-end pipelines for AI and Machine Learning and in particular the data layer underlying the pipelines (e.g., DVC, Pachyderm, Common Metadata Framework)
  • Experience in AI model development lifecycle, ML/deep learning frameworks and MLOps platforms (e.g. Pytorch/Tensorflow, MLFlow, Kubeflow, Ray)
  • Experience with agentic AI platforms (e.g., LangGraph, CrewAI, ADK, LlamaIndex, etc.)
Preferred Skills
  • Strong programming skills in Python with high proficiency in data structures and algorithms. C/C++ skills
  • Experience with CI/CD code development
  • Outstanding analytical and problem-solving skills
  • Experience with hybrid AI-HPC workflows (e.g., AI surrogate modeling, computational steering of experiments)
  • Experience with knowledge graphs and knowledge infused learning
  • Expertise in research of data and workflow management systems
  • Experience in system software performance and scalability optimization
  • Experience with multi-threaded programming, parallel processing, OOD/OOP/distributed programming
  • Experience in containerized development and orchestration tools (e.g. Kubernetes, Ezmeral)

Additional Skills:

Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security-First Mindset

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

#unitedstates

Job:

Engineering

Job Level:

TCP_03"The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
- United States of America: Annual Salary USD 126,500 - 240,500 in Colorado
The listed salary range reflects base salary. Variable incentives may also be offered."

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

The estimated job application period closure is June 1 2026; this timeline is provided for transparency and internal planning purposes.

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

No Fees Notice & Recruitment Fraud Disclaimer

It has come to HPE's attention that there has been an increase in recruitment fraud whereby scammer impersonate HPE or HPE-authorized recruiting agencies and offer fake employment opportunities to candidates. These scammers often seek to obtain personal information or money from candidates.

Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendorswill never charge any candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process.The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candidates and candidates shall be solely responsible to conduct such verification. Any candidate/individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that may result from any such communication.


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