ZipRecruiter

Log In

1

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 ...

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 ...

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 · On-site

$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 ...

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 Jul 14, 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.

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, 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.
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 July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

AI & Machine Learning Engineer

V-Work Infotech Solutions INC

Cape Coral, FL • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary

We are seeking an experienced AI & Machine Learning Engineer with 10–15+ years of IT experience to design, develop, and deploy scalable AI and machine learning solutions. The ideal candidate will have expertise in Generative AI, Large Language Models (LLMs), deep learning, MLOps, cloud platforms, and production-grade AI systems. You will collaborate with data scientists, software engineers, and business stakeholders to deliver AI-driven products and intelligent automation solutions.

Key Responsibilities
  • Design, develop, and deploy machine learning and Generative AI solutions.
  • Build, fine-tune, and optimize Large Language Models (LLMs) and foundation models.
  • Develop Retrieval-Augmented Generation (RAG) applications.
  • Design AI architectures for enterprise-scale applications.
  • Build end-to-end ML pipelines from data ingestion to model deployment.
  • Develop AI-powered chatbots, virtual assistants, and recommendation systems.
  • Implement prompt engineering techniques to improve LLM performance.
  • Deploy models using MLOps best practices.
  • Optimize model accuracy, latency, scalability, and cost.
  • Work with structured, semi-structured, and unstructured datasets.
  • Collaborate with Data Engineering teams to build scalable AI platforms.
  • Monitor production AI systems and continuously improve model performance.
  • Ensure AI solutions follow security, governance, and responsible AI practices.
  • Mentor junior engineers and provide technical leadership.
Required Qualifications
  • Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
  • 10–15+ years of IT experience, with significant experience in AI/ML engineering.
  • Strong understanding of machine learning algorithms, deep learning, and Generative AI.
  • Experience delivering enterprise AI solutions.
  • Excellent communication and problem-solving skills.

Apply