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Machine Learning Computational Chemistry Jobs in Colorado

Cymertek Corporation

Data Scientist

Aurora, CO · On-site

$100 - $160/hr

... Machine Learning Engineer, AI Specialist, Statistician, Data Engineer, Business Intelligence Analyst, Quantitative Analyst, Research Scientist, Predictive Analytics Specialist, Computational ...

Cymertek

Data Scientist

Aurora, CO · On-site

... Machine Learning Engineer, AI Specialist, Statistician, Data Engineer, Business Intelligence Analyst, Quantitative Analyst, Research Scientist, Predictive Analytics Specialist, Computational ...

Cymertek

Data Scientist / Software Engineer

Aurora, CO · On-site

... Computational Science, Electrical Engineering, Machine Learning, ect. ALTERNATE EXPERIENCE General comment on degrees: Most contracts allow additional experience (4-5 years) in lieu of a Bachelor ...

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All JobsMachine Learning Computational Chemistry JobsMachine Learning Computational Chemistry Jobs in Colorado

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:

Machine Learning Computational Chemistry jobs near you

Principal Researcher for AI Risk Management

Sensor Science Division | NIST

Boulder, CO • On-site

$118K/yr

Full-time

Posted 4 days ago

Job description

NIST is seeking an AI risk management expert to drive national leadership in trustworthy AI technology. You will maintain NIST's AI Risk Management Framework (AI RMF), develop related ITL guidelines such as the AI RMF Playbook, and foster community engagement to promote widespread AI RMF adoption and help others manage AI risk across sectors.
This notice is issued under direct-hire authority to recruit new talent to occupations for which NIST has a severe shortage of candidates.

Qualifications:For the Computer Scientist ZP-1550
Basic Requirements:
Bachelor's degree in computer science or bachelor's degree with 30 semester hours in a combination of mathematics, statistics, and computer science. At least 15 of the 30 semester hours must have included any combination of statistics and mathematics that included differential and integral calculus. All academic degrees and coursework must be from accredited or pre-accredited institutions.
For the ZP-1550-IV: In addition to the above basic requirements, applicants must have one year (52 weeks) of specialized experience at the GS-12 level (ZP-III at NIST). The specialized experience is defined as:
  • Experience conducting technical research or development work to study or implement artificial intelligence (AI) and machine learning (ML) tools.
  • Experience drafting technical papers, guidelines, or standards intended to guide a broad community of AI/ML practitioners regarding best practices for applying AI/ML and managing AI/ML risk, either from a computational or behavioral and social sciences perspective.
  • Experience serving as a technical representative or coordinator in multi-stakeholder or interagency technology-related fora, such as working groups or standards committees.
For the ZP-1550-V: In addition to the above basic requirements, applicants must have one year (52 weeks) of specialized experience at the GS-14 level (ZP-IV at NIST). The specialized experience is defined as:
  • Experience conducting technical research or development work to study or implement artificial intelligence (AI) and machine learning (ML) tools.
  • Experience formulating, leading, or managing complex computer science projects or technology policy initiatives of considerable scope and impact related to AI/ML.
  • Experience developing and authoring technical papers, guidelines, or standards intended to guide a broad community of AI/ML practitioners regarding best practices for applying AI/ML and managing AI/ML risk, leveraging either computational or behavioral and social sciences perspectives.
  • Experience leading collaborative work in multi-stakeholder or interagency technology-related fora, such as working groups or standards committees, to influence technology programs or technical consensus.

For the Social Scientist ZP-0101
Basic Requirements:
Degree: behavioral or social science; or related disciplines appropriate to the position.
OR
A combination of education and experience that provided the applicant with knowledge of one or more of the behavioral or social sciences equivalent to a major in the field.
OR
Four years of appropriate experience that demonstrated that the applicant has acquired knowledge of one or more of the behavioral or social sciences equivalent to a major in the field.
For the ZP-0101-IV: In addition to the above basic requirements, applicants must have one year (52 weeks) of specialized experience at the GS-12 level (ZP-III at NIST). The specialized experience is defined as:
  • Experience conducting technical research or development work to study or implement artificial intelligence (AI) and machine learning (ML) tools.
  • Experience drafting technical papers, guidelines, or standards intended to guide a broad community of AI/ML practitioners regarding best practices for applying AI/ML and managing AI/ML risk, either from a computational or behavioral and social sciences perspective.
  • Experience serving as a technical representative or coordinator in multi-stakeholder or interagency technology-related fora, such as working groups or standards committees.
For the ZP-0101-V: In addition to the above basic requirements, applicants must have one year (52 weeks) of specialized experience at the GS-14 level (ZP-IV at NIST). The specialized experience is defined as:
  • Experience conducting technical research or development work to study or implement artificial intelligence (AI) and machine learning (ML) tools.
  • Experience formulating, leading, or managing complex computer science projects or technology policy initiatives of considerable scope and impact related to AI/ML.
  • Experience developing and authoring technical papers, guidelines, or standards intended to guide a broad community of AI/ML practitioners regarding best practices for applying AI/ML and managing AI/ML risk, leveraging either computational or behavioral and social sciences perspectives.
  • Experience leading collaborative work in multi-stakeholder or interagency technology-related fora, such as working groups or standards committees, to influence technology programs or technical consensus.

Experience includes paid and unpaid experience, including volunteer work through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional, philanthropic, religious, spiritual, community, student, social). Volunteer work helps build critical competencies, knowledge, and skills, and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience. The qualification requirements in this vacancy announcement are based on the U.S. Office of Personnel Management (OPM) Qualification Standards Handbook. If requesting reconsideration of your qualification determination, please refer to the following site: Applicant ReconsiderationEducation:Social Scientist, ZP-0101: This position allows applicants to qualify with education. Transcripts must be submitted to validate that the education requirement has been met. Unofficial transcripts will be accepted in the application package. However, an official copy will be required before a final offer of employment.
Computer Scientist, ZP-1550: This position has an education requirement. Transcripts must be submitted to validate that the education requirement has been met. Unofficial transcripts will be accepted in the application package. However, an official copy will be required before a final offer of employment.
Use of foreign education for qualifications. An accredited organization must evaluate education completed outside of the U.S. to ensure that it is comparable to education received in accredited institutions in the U.S. Click here to view a listing of accredited organizations from the Department of Education's website. A copy of the foreign education evaluation (containing the results with a course-by-course listing) is required with your application.Employment Type: OTHER

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