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Neuroscience Ai Machine Learning Jobs in Colorado

Nou Systems Inc

Machine Learning Engineer

Colorado Springs, CO · On-site

$100K - $160K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are pleased to announce an opening for a Machine Learning Engineer who will join our team in ... Experience with LLMs, generative AI tools, vector databases, or frameworks such as LangChain or ...

Lockheed Martin

$89K - $157K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Space AI Talent Center is seeking a highly skilled AI/ML Machine Learning Engineer to join a cross-functional team of experts in research, data science, software development, physics, and ...

Booz Allen Hamilton

Computer Scientist, Senior

Aurora, CO

$99K - $225K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Your deep analytics, data science, AI, and machine learning expertise and consulting mindset, coupled with an original approach to your work, will help clients and stakeholders make sense of their ...

New

Booz Allen Hamilton

Senior Computer Scientist

Aurora, CO · On-site

$99K - $225K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Your deep analytics, data science, AI, and machine learning expertise and consult ing mindset, coupled with an original approach to your work, will help clients and stakeholders make sense of their ...

New

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Neuroscience Ai Machine Learning information

See Colorado salary details

$26.8K

$44.8K

$92.5K

How much do neuroscience ai machine learning jobs pay per year?

As of Aug 13, 2026, the average yearly pay for neuroscience ai machine learning in Colorado is $44,777.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,200.00 and $48,400.00 per year, depending on experience, location, and employer.

What are common challenges faced by professionals working in Neuroscience AI and Machine Learning, and how can they be addressed?

Professionals in Neuroscience AI and Machine Learning often encounter challenges such as integrating complex neural data with AI models, handling large and noisy datasets, and ensuring their algorithms are interpretable and clinically relevant. Collaborating closely with neuroscientists, clinicians, and data engineers is essential to address these hurdles. Staying updated on the latest research, leveraging robust data preprocessing techniques, and participating in interdisciplinary team meetings can help overcome these challenges and contribute to innovative solutions in the field.

What is the difference between Neuroscience Ai Machine Learning vs Data Scientist?

AspectNeuroscience Ai Machine LearningData Scientist
Required CredentialsBackground in neuroscience, AI, machine learning, programming skillsDegree in data science, statistics, computer science, or related fields
Work EnvironmentResearch labs, healthcare, biotech, academiaTech companies, finance, marketing, healthcare
Industry UsageNeuroscience research, AI development for brain-related applicationsData analysis, predictive modeling, business insights across industries

Neuroscience Ai Machine Learning focuses on applying AI and machine learning techniques specifically to neuroscience research and brain-related applications, often requiring specialized knowledge in neuroscience. Data Scientists have a broader scope, working with data analysis and modeling across various industries. While both roles involve machine learning skills, their focus areas and work environments differ significantly.

What are the key skills and qualifications needed to thrive as a Neuroscience AI Machine Learning specialist?

To thrive as a Neuroscience AI Machine Learning Specialist, you need a strong background in neuroscience, machine learning, and data analysis, often supported by an advanced degree in a related field (e.g., neuroscience, computer science, or bioinformatics). Expertise in programming languages like Python or MATLAB, familiarity with deep learning frameworks (such as TensorFlow or PyTorch), and experience with neuroimaging tools are typically required. Strong problem-solving abilities, curiosity, and effective interdisciplinary communication are valuable soft skills. These competencies are essential for innovatively analyzing complex neural data and developing AI-driven solutions that advance neuroscience research.

What is a Neuroscience AI Machine Learning specialist?

A Neuroscience AI Machine Learning specialist is a professional who applies artificial intelligence and machine learning techniques to analyze and interpret data related to the brain and nervous system. They work at the intersection of neuroscience, computer science, and data science to develop models that can help understand brain function, diagnose neurological disorders, or advance brain-computer interface technologies. Their work often involves processing complex datasets such as brain imaging or neural recordings, and building predictive models that contribute to both scientific discovery and healthcare innovation.
What are popular job titles related to Neuroscience Ai Machine Learning jobs in Colorado? For Neuroscience Ai Machine Learning jobs in Colorado, the most frequently searched job titles are:
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What cities in Colorado are hiring for Neuroscience Ai Machine Learning jobs? Cities in Colorado with the most Neuroscience Ai Machine Learning job openings:
Neuroscience Ai Machine Learning jobs near you

AI Trainer - Microbiology Expert

micro1 AI

Pueblo, CO • Remote

$70 - $90/hr

Part-time

Posted 15 days ago

Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelor’s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Master’s or PhD) in a relevant field.

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