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Neuroscience Ai Machine Learning Jobs in Georgia

Metas Solutions

AI/Machine Learning Engineer

Decatur, GA · On-site

$95K - $130K/yr

Bachelor's degree in technology, Engineering, or Computer Science.8+ years of experience designing, developing, and deploying machine learning models8+ years of experience with Generative AI, LLMs ...

innovitusa

Machine Learning Engineer

Atlanta, GA

W2 Candidates Only We are seeking a Machine Learning Engineer to develop, deploy, and optimize machine learning models and AI solutions. The ideal candidate will have strong experience with Python ...

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 ...

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 ...

Cox Automotive

Machine Learning Lead Engineer

Vinnings, GA · On-site

$134K - $224K/yr

Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business ...

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

As of Aug 31, 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 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 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 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 popular job titles related to Neuroscience Ai Machine Learning jobs in Georgia?

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Cities in Georgia with the most Neuroscience Ai Machine Learning job openings:

Neuroscience Ai Machine Learning jobs near you

Vertex AI Machine Learning Architect

CirrusLabs

Alpharetta, GA • On-site

Full-time

Re-posted 9 days ago

Job description

Job Summary:
CirrusLabs is a niche digital transformation company focused on innovation and co-creating success with its customers. They are seeking a Vertex AI Machine Learning Architect to develop, deploy, and manage machine learning models using Google Cloud's Vertex AI platform, while collaborating with teams to implement AI solutions that solve complex business problems.
Responsibilities:
• Design, develop, and deploy machine learning models using Vertex AI.
• Integrate Vertex AI with other Google Cloud services such as AlloyDB, BigQuery, Cloud Storage, and Dataflow.
• Utilize AutoML capabilities to create high-quality models with minimal manual effort.
• Develop custom training pipelines for more complex machine learning tasks using frameworks like TensorFlow and PyTorch.
• Implement and manage Vertex AI Pipelines for orchestrating end-to-end machine learning workflows.
• Monitor and optimize model performance post-deployment, ensuring models remain accurate and efficient over time.
• Collaborate with data scientists, software engineers, and other stakeholders to understand business requirements and translate them into effective AI solutions.
• Perform hyperparameter tuning to enhance model performance.
• Utilize Vertex AI Feature Store for feature management and reuse.
• Conduct online and batch predictions using Vertex AI prediction services.
• Adhere to MLOps best practices for model versioning, deployment, and lifecycle management.
Qualifications:
Required:
• Proven experience with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Hands-on experience with Google Cloud Platform (Google Cloud Platform) services, specifically Vertex AI.
• Strong programming skills in Python or a similar language.
• Familiarity with data processing tools like Apache Beam, Dataflow, or similar.
• Understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
• Experience with AutoML tools and techniques.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.
• Strong communication and collaboration skills.
Company:
CirrusLabs is an IT company provides agile software delivery, automation, cloud Services, and IoT. Founded in 2005, the company is headquartered in Alpharetta, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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