2

Remote Neural Monitoring Jobs in California (NOW HIRING)

... the neural systems involved, with a focus on enhancing fear extinction and related learning ... Help administer, pilot, and monitor remote psychophysiological fear-conditioning paradigms ...

Set up, monitor, and troubleshoot psychophysiological recording sessions using systems such as ... remote photoplethysmography (PPG) signals derived from video . * Conduct and score clinical ...

Set up, monitor, and troubleshoot psychophysiological recording sessions using systems such as ... remote photoplethysmography (PPG) signals derived from video . * Conduct and score clinical ...

Remote Neural Monitoring information

What are the key skills and qualifications needed to thrive in the remote neural monitoring position, and why are they important?

To thrive as a Remote Neural Monitoring Specialist, you need an advanced understanding of neuroscience, electrophysiology, and experience with neural data acquisition, typically supported by a relevant degree in biomedical engineering, neuroscience, or a related field. Familiarity with brain-computer interface (BCI) systems, neural data analysis software, and compliance with institutional review board (IRB) protocols or other regulatory standards is essential. Strong problem-solving skills, attention to detail, and the ability to communicate complex technical information clearly set top candidates apart. These skills ensure accurate data interpretation, adherence to ethical standards, and effective collaboration within interdisciplinary research or clinical teams.

What are the primary responsibilities and challenges faced by a remote neural monitoring specialist?

As a Remote Neural Monitoring Specialist, your primary responsibilities include continuously tracking neural activity data from patients or research subjects, ensuring the integrity and quality of data, and providing real-time feedback to clinical or research teams. One of the main challenges in the role is accurately identifying significant neural events or anomalies while minimizing false positives, which requires both technical expertise and focused attention. You may also need to troubleshoot technical issues with monitoring equipment or software remotely and maintain strict compliance with privacy and ethical guidelines. Collaboration with physicians, neuroscientists, or IT professionals is common, ensuring comprehensive care or data analysis. This role offers opportunities to advance into project management, clinical lead positions, or specialize in emerging neurotechnology fields.

What is remote neural monitoring?

Remote Neural Monitoring (RNM) is a concept often associated with surveillance theories rather than an established job role. It is sometimes described as technology that can remotely track neural activity, but there is no verified scientific basis for such a profession. If you're looking for careers in neuroscience, artificial intelligence, or brain-computer interfaces, consider roles in neurotechnology research, cognitive science, or biomedical engineering. Always verify job listings with reputable sources to avoid misinformation.

What cities in California are hiring for Remote Neural Monitoring jobs? Cities in California with the most Remote Neural Monitoring job openings:
Infographic showing various Remote Neural Monitoring job openings in California as of July 2026, with employment types broken down into 81% Full Time, 8% Part Time, and 11% Contract. Highlights an 100% Remote job distribution.

Machine Learning Engineer : 26-02124

Akraya Inc.

Pleasanton, CA • On-site, Remote

$55 - $60/hr

Temporary

Posted 16 days ago


Job description


Primary Skills: Machine Learning (Expert), Python & SQL (Expert), Deep Learning & NLP (Advanced), Azure AI/ML (Advanced), MLOps & DevOps (Advanced)
Contract Type: W2 Only
Duration: 6+ Months
Location: Pleasanton, CA. Hybrid/Remote (Must Support PST Hours)
Pay Range:$55 - $60 on W2
Job Summary:
We are seeking an experienced Machine Learning Engineer to design, develop, deploy, and optimize scalable machine learning solutions for enterprise applications. The ideal candidate will have strong expertise in supervised and unsupervised learning, deep learning, natural language processing (NLP), and cloud-based AI platforms, with hands-on experience deploying production-ready ML models using Azure and MLOps best practices.
Key Responsibilities:
  • Design, develop, train, and deploy machine learning models for predictive analytics and intelligent automation.
  • Build and optimize supervised and unsupervised learning models to solve complex business problems.
  • Develop deep learning solutions using neural networks and NLP techniques.
  • Create data pipelines for feature engineering, model training, validation, and inference.
  • Deploy, monitor, and maintain ML models using Azure cloud services and MLOps best practices.
  • Collaborate with Data Scientists, Data Engineers, and business stakeholders to translate requirements into scalable AI solutions.
  • Optimize model performance, accuracy, scalability, and reliability through continuous experimentation and tuning.
  • Develop reusable Python libraries, APIs, and automation scripts for ML workflows.
  • Implement CI/CD pipelines and DevOps practices for model deployment, versioning, and lifecycle management.
  • Document technical designs, model architectures, and deployment processes while following enterprise development standards.
Must-have Skills:
  • 5+ years of experience developing and deploying Machine Learning solutions.
  • Strong expertise in Supervised and Unsupervised Machine Learning Algorithms.
  • Hands-on experience with Neural Networks and Natural Language Processing (NLP).
  • Advanced programming skills in Python, SQL, and R.
  • Experience with machine learning frameworks including TensorFlow, Keras, and PyTorch.
  • Strong experience with Microsoft Azure AI/ML services and cloud-based model deployment.
  • Hands-on knowledge of DevOps and MLOps practices, including CI/CD pipelines and model lifecycle management.
  • Experience with data preprocessing, feature engineering, model evaluation, and hyperparameter tuning.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to work independently while collaborating with cross-functional technical teams.
Nice-to-have Skills:
  • Experience with Azure Machine Learning, Azure Databricks, or Azure OpenAI Services.
  • Familiarity with containerization technologies such as Docker and Kubernetes.
  • Experience building REST APIs for ML model serving.
  • Knowledge of Git, version control, and automated deployment pipelines.
  • Experience working in Agile/Scrum environments and enterprise AI initiatives.
ABOUT AKRAYA
Akraya is an award-winning IT staffing firm consistently recognized for our commitment to excellence and a thriving work environment. Most recently, we were recognized Stevie Employer of the Year 2025, SIA Best Staffing Firm to work for 2025, Inc 5000 Best Workspaces in US (2025 & 2024) and Glassdoor's Best Places to Work (2023 & 2022)!
Industry Leaders in Tech Staffing
As Talent solutions provider for Fortune 100 Organizations, Akraya's industry recognitions solidify our leadership position in the IT staffing space. We don't just connect you with great jobs, we connect you with a workplace that inspires!
Join Akraya Today!
Let us lead you to your dream career and experience the Akraya difference. Browse our open positions and join our team!

Akraya logo

About Akraya

Sourced by ZipRecruiter

Akraya is an award-winning IT staffing firm and the staffing partner of choice for many leading companies across the US. Akraya was recently voted as a 2021 Best Staffing Firm to Temp for by Staffing Industry Analysts and voted by our employees and consultants as a 2022 Glassdoor Best Places to Work.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

Santa Clara, CA, US

Year founded

2001