ZipRecruiter

Log In

1

Neuroscience Ai Machine Learning Jobs in Georgia

Ksb

Machine Learning Engineer

Grovetown, GA · On-site

You'll work at the intersection of machine learning and the physical world to build AI systems that learn from real industrial data and connect with the engineering models behind them. The role lives ...

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

$120 - $165/hr

Machine Learning Engineer Employment Type: Full Time Location: Atlanta, GA Description We are ... You will work closely with AI/ML researchers, data engineers, and product teams to design ...

Equifax, Inc.

Machine Learning Engineer

Atlanta, GA · On-site

Equifax is excited to add a Machine Learning Engineer to our team. What you'll do * Design complex ... AI/ML coursework preferred * 7+ years of related work experience, including proven experience ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

next page

Showing results 1-20

All JobsNeuroscience Ai Machine Learning JobsNeuroscience Ai Machine Learning Jobs in Georgia

Neuroscience Ai Machine Learning information

See Georgia salary details

$21.5K

$36K

$74.3K

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

As of Aug 8, 2026, the average yearly pay for neuroscience ai machine learning in Georgia is $35,957.00, according to ZipRecruiter salary data. Most workers in this role earn between $27,400.00 and $38,800.00 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 Georgia? For Neuroscience Ai Machine Learning jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Neuroscience Ai Machine Learning jobs in Georgia look for? The top searched job categories for Neuroscience Ai Machine Learning jobs in Georgia are:
What cities in Georgia are hiring for Neuroscience Ai Machine Learning jobs? Cities in Georgia with the most Neuroscience Ai Machine Learning job openings:
Neuroscience Ai Machine Learning jobs near you

Business Analyst (AI / Machine Learning) - New York, NY / Alpharetta, GA

NMK Global Inc.

Milton, GA • On-site

Other

Posted 10 days ago

Job description

Hi Every one,
Hope doing well!.

Job Description: Business Analyst (AI / Machine Learning)

Location: New York, NY / Alpharetta, GA (Hybrid / Onsite)

Exp:6-8+Years.

Position Summary

We are looking for a Business Analyst with AI experience to bridge the gap between our business teams and technology teams. In this role, you will analyze business operations, identify opportunities to apply Artificial Intelligence (AI) and Machine Learning (ML) solutions, and help translate business needs into technical specifications for our data science and engineering teams.

Key Responsibilities

  • Gather & Translate Requirements: Work with business stakeholders to understand their goals and translate them into functional/technical requirements for AI models and software teams.

  • Identify AI Use Cases: Analyze business processes to identify areas where AI/ML, automation, or predictive analytics can improve efficiency and user experience.

  • Process & Data Analysis: Review business workflows and data sources to assess feasibility for AI integration.

  • Collaborate with Tech Teams: Partner with Data Scientists, ML Engineers, and Software Developers to guide product design and build features.

  • User Acceptance Testing (UAT): Design test scenarios, validate AI model outputs against business needs, and ensure product quality.

  • Documentation & Communication: Create process maps, wireframes, user stories, and documentation to keep stakeholders aligned.

Required Qualifications

  • Experience: 3+ years of experience as a Business Analyst (or Systems Analyst / Data Analyst).

  • AI/ML Familiarity: Proven experience working on projects that involve AI, Machine Learning, Generative AI, or Advanced Analytics.

  • Agile Methodology: Strong experience writing User Stories, managing backlogs, and working in Agile/Scrum teams.

  • Data Skills: Proficient in SQL and basic data analysis tools (Excel, Tableau, or Power BI) to query and analyze data.

  • Communication: Excellent verbal and written communication skills to present technical concepts to non-technical business partners.

  • Education: Bachelor s degree in Business, Computer Science, Data Analytics, or a related field.

Preferred / Nice-to-Have Skills

  • Familiarity with Generative AI tools, LLMs, or prompt engineering frameworks.

  • Experience with cloud platforms (AWS, Azure, or Google Cloud Platform).

  • Certification in Business Analysis (CBAP, PMI-PBA) or Agile (CSPO, CSM).

Apply