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Neuroscience Ai Machine Learning Jobs (NOW HIRING)

Merican

AI / Machine Learning Engineer

PA · On-site

AI / Machine Learning Engineer (Contract) Location: Philadelphia, PA or Charlotte, NC Duration: 6 Months Contract Job Summary We are seeking an experienced AI / Machine Learning Engineer to design ...

Cogent Info

AI/ Machine Learning Engineer

Austin, TX · On-site

$96K - $132K/yr

Mid-Level AI/Machine Learning Engineer Join one of the top 10 global powerhouses transforming the future of Market. As an AI / Machine Learning Engineer, you'll play a key role in designing ...

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 ...

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 · On-site +1

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

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Neuroscience Ai Machine Learning information

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$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

Merican Inc

Pittsburgh, PA • On-site

Other

Posted 6 days ago

Job description

Job Title: AI / Machine Learning Engineer (Contract)

Location: Philadelphia, PA or Charlotte, NC
Duration: 6 Months Contract

Job Summary

We are seeking an experienced AI / Machine Learning Engineer to design, develop, and deploy scalable AI and Large Language Model (LLM) solutions within enterprise AWS environments. The ideal candidate will have hands-on expertise with LangChain and LangGraph, strong Python development skills, and experience building production-grade AI applications that are reliable, secure, and high-performing.

Key Responsibilities
  • Design, develop, and deploy AI/LLM-powered applications in AWS production environments.
  • Build, orchestrate, and manage intelligent workflows using LangChain and LangGraph.
  • Integrate AI solutions with enterprise applications, APIs, and data platforms.
  • Optimize model performance, latency, scalability, and reliability for production use cases.
  • Develop and implement prompt engineering strategies and model evaluation frameworks.
  • Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.
  • Ensure adherence to software engineering best practices, including CI/CD, version control, testing, and deployment automation.
  • Monitor, troubleshoot, and enhance AI applications in production environments.
Required Qualifications
  • Proven experience deploying and supporting applications in AWS production environments (e.g., Lambda, ECS, EKS, S3).
  • Hands-on experience with LangChain and LangGraph for AI orchestration and workflow development.
  • Strong programming experience in Python.
  • Experience working with Large Language Models (LLMs), prompt engineering, and model evaluation techniques.
  • Solid understanding of software development best practices, including CI/CD pipelines, Git-based version control, automated testing, and deployment processes.
  • Experience integrating AI solutions with enterprise systems and APIs.
Preferred Qualifications
  • Experience building and deploying scalable generative AI applications.
  • Familiarity with vector databases, RAG (Retrieval-Augmented Generation), and AI observability tools.
  • Understanding of cloud security, governance, and compliance considerations for AI workloads.
  • Experience working in Agile development environments.
Work Arrangement
  • Candidates must be available to work onsite during the first week (Monday Friday).
  • Candidates located in Philadelphia, PA or Charlotte, NC will follow a hybrid schedule, working onsite with the team three days per week after onboarding.
Employment Type
  • Contract (6 Months)

If you are passionate about building production-ready AI solutions and have strong expertise in AWS, LangChain, and LangGraph, we encourage you to apply.

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About Merican

Sourced by ZipRecruiter

Merican is a IT Service consulting firm, specialized in Digital adoption and Business automation. With our diverse collection of skilled and committed consultants, technology companies, businesses and digital experts, we provide our subject expertise and our unique client service approach, a best-in-class global model of delivery suited to the business demands of our clients. We ensure that we implement future-oriented solutions for our clients via investments in people, solutions, technologies, competencies and infrastructure.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Columbia , MD, US

Year founded

2020

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