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Neuro Data Engineer Jobs (NOW HIRING)

Weekday AI

Neurologist

$82 - $287/hr

Work alongside AI developers to train and assess machine learning models focused on neurological ... Strong knowledge of data annotation and quality assurance processes. * A background in both adult ...

LVIS

Senior DevOps Engineer

Palo Alto, CA · On-site

$150K - $200K/yr

... neurology health care industry. LVIS is looking for a senior DevOps engineer who is responsible for commercial cloud-based big-data-driven medical analysis software in the cloud and management for ...

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Neuro Data Engineer information

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$44.5K

$129.7K

$177.5K

How much do neuro data engineer jobs pay per year?

As of Jun 6, 2026, the average yearly pay for neuro data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Neuro Data Engineer, and why are they important?

To thrive as a Neuro Data Engineer, you need strong expertise in neuroscience, data analysis, and programming skills (often in Python or MATLAB), typically backed by a degree in computer science, neuroscience, or a related field. Familiarity with neuroimaging tools (like fMRI or EEG analysis software), machine learning frameworks, and big data platforms is highly valuable. Excellent problem-solving, collaboration, and communication skills help in translating complex neural data into actionable insights for research or clinical applications. These competencies are crucial for ensuring accurate data handling, effective interdisciplinary teamwork, and advancement in neurotechnology projects.

What are Neuro Data Engineers?

Neuro Data Engineers are specialized professionals who design, develop, and maintain data systems that support neuroscience research and applications. They work at the intersection of data engineering and neuroscience, handling large and complex datasets such as brain imaging, neural recordings, and genetic data. Their responsibilities include building data pipelines, ensuring data quality, and collaborating with neuroscientists to enable efficient analysis and interpretation of neural data. By leveraging advanced technologies and programming skills, Neuro Data Engineers help accelerate discoveries in brain research and related fields.

How do Neuro Data Engineers typically collaborate with neuroscientists and clinical teams in research environments?

Neuro Data Engineers often work closely with neuroscientists and clinical professionals to design data pipelines, manage large-scale neural datasets, and ensure data quality for research studies. Collaboration includes translating scientific requirements into technical solutions, supporting data preprocessing, and developing analytical tools tailored to neuroscience workflows. Regular meetings, code reviews, and interdisciplinary workshops are common, fostering a team environment where technical and scientific expertise are integrated to drive research forward.

What is the difference between Neuro Data Engineer vs Data Scientist?

AspectNeuro Data EngineerData Scientist
Required CredentialsBachelor's or Master's in Neuroscience, Computer Science, or related fields; experience with data engineering toolsBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming and analytics
Work EnvironmentNeuroscience labs, research institutions, healthcare settingsTech companies, research firms, finance, healthcare
Employer & Industry UsageNeuroscience research, neurotechnology companies, healthcare providersTech firms, consulting, research, analytics

Neuro Data Engineers focus on building and maintaining data pipelines for neuroscience data, while Data Scientists analyze data to extract insights. Both roles require strong technical skills, but Neuro Data Engineers emphasize data infrastructure in neuroscience contexts, whereas Data Scientists focus on data analysis and modeling across industries.

Infographic showing various Neuro Data Engineer job openings in the United States as of May 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 100% In-person job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Artificial Intelligence Engineer II

Artificial Intelligence Engineer II

Baylor College of Medicine

Houston, TX

$109K - $131K/yr

Full-time

Posted yesterday

Baylor College of Medicine rating

8.6

Company rating: 8.6 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

50th of 532 rated colleges and universities

Job description

Summary

The department of Neurology at Baylor College of Medicine is looking for an experienced Artificial Intelligence Engineer II to support Dr. Ihab Hajjar. In this position, you will support the development and evaluation of machine learning and natural language processing systems for clinical research applications, with a focus on building reproducible data pipelines, analyzing multimodal data (e.g., speech and text), and contributing to model design, validation, and deployment. The role emphasizes collaboration with interdisciplinary teams and adherence to data governance and research standards while advancing methods relevant to AI engineering and research.

Job Duties

Machine Learning Systems & AI Engineering – 30%

  • Develop and maintain pipelines (Python-based) for data processing, feature extraction, and model evaluation.
  • Implement and test machine learning and NLP models, including training, fine-tuning, and benchmarking. 
  • Conduct error analysis and iterative model improvement using structured experiments. 
  • Build modular, reusable code to support reproducible experiments and configuration-driven workflows. 

Data Management, Quality Control, and Reproducibility -30% 

  • Perform exploratory data analysis to assess data quality.
  • Implement validation checks, logging, and documentation to ensure data integrity and traceability.
  • Maintain structured datasets and features to support reproducible research workflows.
  • Support versioning and organization of data and model artifacts. 

Deployment, Inference, and Monitoring – 20%

  • Support model deployment in batch or research-oriented environments.
  • Implement and monitor inference workflows, including runtime performance and reliability.
  • Assist with maintaining pipelines as models or APIs evolve. 
  • Contribute to improving efficiency, scalability, and robustness of model execution. 

Responsible AI, Security, and Compliance – 10%

  • Follow institutional policies for handling PHI and sensitive research data. 
  • Apply best practices for data security, access control, and safe logging.
  • Document model limitations, assumptions, and validation procedures.
  • Support responsible use of AI systems in clinical research settings. 

Collaboration, Communication, and Development -10%

  • Collaborate with clinical and technical team members on research projects.
  • Summarize methods, results, and risks for mixed audiences. 
  • Contribute to figures, tables, and written materials for reports or publications. 
  • Stay current with developments in machine learning, NLP, and AI systems. 
  • Perform other job-related duties as assigned. 
     
Minimum Qualifications
  • Bachelor’s degree in Computer Sciences, Statistics, Mathematics, or a related field.
  • Two years of relevant experience.
Preferred Qualifications
  • Master’s degree in Computer Sciences, Statistics, Mathematics, or a related field.

Work Authorization Requirement:

This position is not eligible for visa sponsorship. Candidates must be legally authorized to work in the United States at the time of application and throughout the duration of employment. 

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.

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