ZipRecruiter

Log In

1

Neuroscience Ai Machine Learning Jobs (NOW HIRING)

Oxy

AI Machine Learning Engineer

Houston, TX

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

Synaptrix Labs

Internship Program

New York, NY

$18.25 - $23.75/hr

... Machine Learning Research, Industrial Design, and UI/UX Design. If you're excited about building the future of brain-computer interfaces and want to work at the intersection of neuroscience, AI, and ...

Elevance Health

AI Machine Learning Scientist

Tampa, FL · Hybrid

AI Machine Learning Scientist Location : This role requires associates to be in-office 1-2 days per week, fostering collaboration and connectivity while providing flexibility to support productivity ...

Oxy

AI Machine Learning Engineer

Houston, TX

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

CyberMedia Technologies

AI / Machine Learning Engineer

$117K - $140K/yr

We are seeking to hire a AI/Machine Learning Engineer to our team! Role Overview: As an AI/ML Engineer for CTEC, you will develop Agentic AI systems designed to automate and optimize health benefits ...

next page

Showing results 1-20

All JobsNeuroscience Ai Machine Learning Jobs

Neuroscience Ai Machine Learning information

See salary details

$25.5K

$42.6K

$88K

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

As of Jun 23, 2026, the average yearly pay for neuroscience ai machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

How to become an AI neuroscientist?

To become an AI neuroscientist, one typically needs a strong educational background in neuroscience, computer science, or related fields, often requiring a PhD or master's degree. Gaining skills in machine learning, programming (such as Python), and data analysis is essential, along with experience in neuroimaging or neural data. Developing expertise in both neuroscience and artificial intelligence enables research at the intersection of these disciplines.

Which 3 jobs will survive AI?

In the field of neuroscience AI and machine learning, roles such as research scientists, data scientists, and AI engineers are likely to persist due to their reliance on complex problem-solving, creativity, and domain expertise. These jobs require advanced knowledge of neuroscience, programming skills, and the ability to interpret and develop new algorithms, making them less susceptible to automation.

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 salary of an AI neuroscientist?

An AI neuroscientist typically earns between $80,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in machine learning and neuroimaging can earn higher salaries, especially in research institutions or tech companies.

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, and why are they important?

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.

Is neuroscience useful for AI?

Neuroscience is useful for AI, especially in developing neural network models inspired by the human brain. Understanding neural processes helps improve machine learning algorithms, pattern recognition, and cognitive computing systems used in AI development.
More about Neuroscience Ai Machine Learning jobs
What cities are hiring for Neuroscience Ai Machine Learning jobs? Cities with the most Neuroscience Ai Machine Learning job openings:
What states have the most Neuroscience Ai Machine Learning jobs? States with the most job openings for Neuroscience Ai Machine Learning jobs include:
What job categories do people searching Neuroscience Ai Machine Learning jobs look for? The top searched job categories for Neuroscience Ai Machine Learning jobs are:
Neuroscience Ai Machine Learning jobs near you
Infographic showing various Neuroscience Ai Machine Learning job openings in the United States as of June 2026, with employment types broken down into 95% Full Time, 1% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
AI/Machine Learning Engineer

AI/Machine Learning Engineer

Initiate Government Solutions

Washington, DC • On-site

$129K - $155K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 15 days ago

Job description

Description:

Founded in 2007, Initiate Government Solutions (IGS) is a Woman-Owned Small Business and a fully remote IT services provider supporting federal partners nationwide. We deliver innovative Enterprise IT and Health Services solutions with a strong focus on data analytics, health informatics, cloud migration, AI, and the modernization of federal information systems.


Our vision is to be a health IT trendsetter, continuing to solve the nation’s most challenging healthcare IT issues by conceiving, designing, and building solid, creative, and innovative open-source solutions.


Our mission is to innovate, design, and deliver tailored solutions that balance technical advancement with cost-awareness while providing exceptional service.


IGS is currently pipelining for a remote AI/Machine Learning Engineer to support our work within the federal healthcare industry. Candidates will be contacted as opportunities become available for further consideration.


Assignment of Work and Travel:

This is a remote access assignment. The Candidate will work remotely daily and will remotely access VA systems and therein use approved VA provided communications systems. Travel is not required; however, the candidate may be required to attend onsite client meetings as requested.


The AI/Machine Learning Engineer will work alongside a team of highly skilled developers and engineers in the development of AI applications. A motivated and qualified candidate will not only have hands-on development experience in (JavaScript, Python or Java) but also a willingness to collaborate with teams to solve problems. Together we’re accelerating our client’s digital transformation through the building and deployment of data-driven, scalable AI solutions.


Responsibilities and Duties (Included but not limited to):

  • Design, develop, and deploy machine learning and deep learning models to support clinical decision-making, predictive analytics, and health outcomes research.
  • Fine-tune models for high performance using healthcare-specific data, including EHRs, claims, imaging, and structured/unstructured text.
  • Collaborate with data engineers to clean, preprocess, and normalize healthcare data in compliance with federal data standards (e.g., HL7, FHIR).
  • Build scalable ML pipelines that integrate with federal data platforms and cloud services (e.g., VA’s Lighthouse API, Azure Government, AWS GovCloud).
  • Ensure AI/ML solutions meet federal regulations, including HIPAA, FISMA, FedRAMP, and VA Information Security requirements.
  • Implement differential privacy, encryption, and access controls to safeguard sensitive health data.
  • Contribute to the development of governance frameworks to ensure transparent, explainable, and bias-mitigated models.
  • Document model lifecycle, from training to deployment, including risk assessments, validation reports, and audit trails.
  • Work cross-functionally with program managers, clinicians, data scientists, and software developers to identify opportunities for AI/ML applications that improve healthcare delivery and veteran outcomes.
  • Present complex machine learning findings in a way that is actionable and aligned with federal healthcare program goals.
  • Stay updated on the latest developments in AI/ML applications for public health and healthcare operations.
  • Prototype and test emerging AI technologies (e.g., NLP for clinical text, computer vision for imaging diagnostics) for possible integration into government systems.
  • Monitor deployed models for drift, accuracy, and operational effectiveness over time.
  • Maintain model retraining schedules based on new data inputs or policy changes.
  • Prepare comprehensive documentation and reports for internal stakeholders and external oversight (e.g., OMB, GAO, IG audits).
  • Develop dashboards and visualizations to track performance metrics, patient outcomes, and utilization trends impacted by AI/ML tools.
Requirements:
  • Bachelor’s degree or higher in one of the following disciplines, Computer Science, Data Science, Artificial Intelligence / Machine Learning, Mathematics / Statistics, Biomedical Engineering, Health Informatics, Electrical or Computer Engineering
  • 4+ years of experience in software and machine learning engineering.
  • Strong knowledge of natural language processing (NLP) and transformer models.
  • 5+ years proficiency in Python and hands-on experience with ML libraries like TensorFlow, PyTorch, or Hugging Face Transformers.
  • Proven experience building scalable, cloud-based AI/ML solutions and enhancing custom question answering mapping/workflows.
  • Expertise in the full ML pipeline, including data processing, model training, serving, and monitoring.
  • Knowledge of NLP architectural strategies such as Retrieval-Augmented Generation, Knowledge Graphs, and Agentic Graphs.
  • Expertise in MLOps best practices, including Infrastructure as Code (IaC), CI/CD pipelines tailored for ML workflows, model version control, and real-time performance monitoring to ensure scalable and reliable AI/ML systems.
  • Familiarity with federal AI governance frameworks and compliance standards (e.g., NIST AI RMF, FedRAMP) is a plus.
  • Passion for developing team-oriented solutions to complex engineering problems
  • Excellent communication skills and attention to detail
  • Analytical mind and problem-solving aptitude
  • Ability to obtain and maintain a Public Trust
  • Strong organizational skills

Preferred Qualifications and Core Competencies:

  • Master’s degree in one of the above-mentioned fields
  • Preferred Tools & Environments: Python, R, TensorFlow, PyTorch, Scikit-learn, AWS (SageMaker), Azure ML, Databricks, Apache Spark, Power BI, Tableau, Plotly, Git, GitHub/GitLab
  • Active VA Public Trust
  • Prior experience supporting a VA program
  • Prior, successful experience working in a remote environment

Successful IGS employees embody the following Core Values:

  • Integrity, Honesty, and Ethics: We conduct our business with the highest level of ethics. Doing things like being accountable for mistakes, accepting helpful criticism, and following through on commitments to ourselves, each other, and our customers.
  • Empathy, Emotional Intelligence: How we interact with others including peers, colleagues, stakeholders, and customers’ matters. We take collective responsibility to create an environment where colleagues and customers feel valued, included, and respected. We work within a diverse, integrated, and collaborative team to drive towards accomplishing the larger mission. We conscientiously and meticulously learn about our customers’ and end-users’ business drivers and challenges to ensure solutions meet not only technical needs but also support their mission.
  • Strong Work Ethic (Reliability, Dedication, Productivity): We are driven by a strong, self-motivated, and results-driven work ethic. We are reliable, accountable, proactive, and tenacious and will do what it takes to get the job done.
  • Life-Long Learner (Curious, Perspective, Goal Oriented): We challenge ourselves to continually learn and improve ourselves. We strive to be an expert in our field, continuously honing our craft, and finding solutions where others see problems.

Compensation: There are a host of factors that can influence final salary, including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications.


Benefits: Initiate Government Solutions offers competitive compensation and a robust benefits package, including comprehensive medical, dental, and vision care, matching 401K and profit sharing, paid time off, training time for personal development, flexible spending accounts, employer-paid life insurance, employer-paid short and long term disability coverage, an education assistance program with potential merit increases for obtaining a work-related certification, employee recognition, and referral programs, spot bonuses, and other benefits that help provide financial protection for the employee and their family.


Initiate Government Solutions participates in the Electronic Employment Verification Program.

Apply