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Remote Neural Engineer Jobs (NOW HIRING)

We're a remote-first culture with operations in North America, Europe, the Middle East, and APAC ... a neural net, but you should know how to use one responsibly. * Solid understanding of data ...

New

Staff AI Engineer

Palo Alto, CA · On-site +1

$215K - $285K/yr

Quartz ranked us the #1 best company for remote workers Responsibilities As we work towards ... statistical and neural methods. * Own the design of evaluation frameworks for offline/online ...

AI Engineer

Pittsburgh, PA · Remote

$70 - $76/hr

Remote - US, Canada, India Salary: $70.00-$76.00/Hourly Role: AI Engineer Primary Skills: Python ... neural network architectures such as Tacotron, FastSpeech, WaveNet, or similar. - Collect ...

Lead AI Developer

$60.50 - $79/hr

Job Role - Lead AI Developer Location - Frisco, Texas(Remote) Note - Submit only Contract to hire ... Knowledge of Neural networks, NLP, GenAI concepts such as RAG & Lang chain, multiagent systems is ...

Quartz ranked us the #1 best company for remote workers Responsibilities As we work towards ... statistical and neural methods * Own the design of evaluation frameworks for offline/online ...

Senior Machine Learning Engineer (Remote)

New York, NY · On-site +1

$114.30K - $157K/yr

You'll join a team of hardworking engineers that are passionate about understanding what drives ... neural networks * Significant experience with machine learning libraries like PyTorch, Tensorflow ...

Staff AI Engineer

Palo Alto, CA · On-site +1

$215K - $285K/yr

Quartz ranked us the #1 best company for remote workers Responsibilities As we work towards ... statistical and neural methods. * Own the design of evaluation frameworks for offline/online ...

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Remote Neural Engineer information

See salary details

$59.5K

$111.6K

$203K

How much do remote neural engineer jobs pay per year?

As of Jun 1, 2026, the average yearly pay for remote neural engineer in the United States is $111,632.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $132,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Neural Engineer, you need a solid background in neuroscience, biomedical engineering, or electrical engineering, often supported by a relevant degree or advanced certification. Proficiency with neural signal processing software, programming languages like Python or MATLAB, and brain-computer interface (BCI) systems is typically required. Strong problem-solving skills, attention to detail, and effective virtual communication are vital soft skills in this role. These skills and qualities are essential for developing, analyzing, and troubleshooting complex neural systems while collaborating with teams remotely.

How do Remote Neural Engineers typically collaborate with cross-functional teams while working off-site?

Remote Neural Engineers frequently use digital collaboration tools such as video conferencing, shared code repositories, and project management platforms to stay connected with colleagues in neuroscience, software development, and data science. Regular virtual meetings and asynchronous communication help ensure alignment on project goals, data analysis, and protocol development. This structure allows for flexibility, but also requires proactive communication and strong organizational skills to manage complex, interdisciplinary tasks from a distance.

What is a Remote Neural Engineer?

A Remote Neural Engineer is a professional who designs, develops, and maintains neural engineering systems—such as brain-computer interfaces or neural prosthetics—while working remotely. They often collaborate with multidisciplinary teams to create solutions that interface with the nervous system, using expertise in neuroscience, biomedical engineering, and software development. Remote Neural Engineers may work from home or distributed locations, utilizing digital tools to analyze neural data, develop algorithms, and contribute to research or product development in the neural technology field.

What is the difference between Remote Neural Engineer vs Remote Data Scientist?

AspectRemote Neural EngineerRemote Data Scientist
Required CredentialsDegree in neuroscience, biomedical engineering, or related fields; knowledge of neural interfacesDegree in computer science, statistics, or related fields; proficiency in data analysis
Work EnvironmentResearch labs, tech companies, healthcare institutions with focus on neural dataTech firms, finance, healthcare, analyzing large datasets
Industry UsageNeuroscience, biomedical engineering, neurotechnologyTechnology, finance, healthcare, research
Common Search/ComparisonYesYes

Remote Neural Engineers focus on developing and implementing neural interfaces and understanding neural systems, often requiring knowledge of neuroscience and biomedical engineering. Remote Data Scientists analyze large datasets to extract insights, typically with skills in statistics and programming. While both roles involve technical expertise and data analysis, Neural Engineers are more specialized in neural technologies, whereas Data Scientists have a broader application across industries.

More about Remote Neural Engineer jobs
What cities are hiring for Remote Neural Engineer jobs? Cities with the most Remote Neural Engineer job openings:
What are the most commonly searched types of Neural Engineer jobs? The most popular types of Neural Engineer jobs are:
What states have the most Remote Neural Engineer jobs? States with the most job openings for Remote Neural Engineer jobs include:
Infographic showing various Remote Neural Engineer job openings in the United States as of May 2026, with employment types broken down into 78% Part Time, and 22% Contract. Highlights an 86% Physical, and 14% Remote job distribution, with an average salary of $111,632 per year, or $53.7 per hour.

Staff ML Application Engineer

Dragos, Inc.

Hanover, MD • Remote

$225K/yr

Other

Posted 2 days ago


Job description

Dragos is on a relentless mission to defend industrial organizations that provide us with the necessities of modern civilization; running water, functioning electricity, and safe industrial working environments. As the market leader in ICS/OT Cybersecurity, we are dedicated to arming our customers with best-in-class technology, threat intelligence, and services to protect their systems as effectively and efficiently as possible. We're a remote-first culture with operations in North America, Europe, the Middle East, and APAC. We're looking for mission-oriented teammates who embody our core values of authenticity, transparency, and trust. Are you ready to make a difference? Come join a mission that can save the world!

About the Role:

We're looking for a Machine Learning Application Engineer to join our Engineering team. This role sits at the intersection of data engineering and applied ML. You'll be taking existing model types and putting them to work inside our product and data pipelines. You won't be training models from scratch or managing ML infrastructure, but you will be doing the thoughtful applied work of figuring out which techniques fit which problems, wiring them into our workflows, and making sure the outputs are reliable and useful.

You'll work closely with AI Engineers, Data Engineers, and product teams to bring ML-driven capabilities into the Dragos platform. Things like clustering network behaviors, classifying assets, and surfacing anomalies that matter for ICS/OT security analysts.

Responsibilities:

  • Apply clustering, classification, anomaly detection, and other established ML techniques to cybersecurity data problems in the ICS/OT domain.
  • Integrate ML model outputs into existing data pipelines and product workflows, supporting both batch and near-real-time processing patterns.
  • Understand model behavior and translate research outputs into reliable pipeline components.
  • Work with Data Engineers to ensure ML-driven stages of the pipeline have clear data contracts, appropriate observability, and sane failure modes.
  • Evaluate open-source and third-party models for fit against specific use cases, knowing when to apply an existing tool versus when to escalate to a model-building effort.
  • Write clean, maintainable Python or Rust that other engineers can reason about, test, and extend.
  • Troubleshoot ML component behavior in production to diagnose issues with output quality, data drift, or unexpected edge cases.
  • Communicate clearly about what a model is doing, where it's uncertain, and how its outputs should (and shouldn't) be used downstream.

Qualifications:

  • 4+ years of software engineering experience, with meaningful time spent working with ML outputs or data pipelines in a production context.
  • Strong Python skills; SQL proficiency; comfort reading and reasoning about data at scale.
  • Hands-on experience applying ML techniques including clustering (k-means, DBSCAN, hierarchical), classification, and anomaly detection.
  • Familiarity with scikit-learn and the surrounding Python ML ecosystem; you don't need to have implemented a neural net, but you should know how to use one responsibly.
  • Solid understanding of data pipeline concepts: how data flows, where it gets transformed, what can go wrong, and how to make failures visible.
  • Ability to evaluate whether a model's outputs are actually trustworthy for a given use case - not just whether accuracy metrics look good.
  • Strong written and verbal communication; comfortable explaining tradeoffs to both technical and non-technical stakeholders.
  • Cybersecurity domain knowledge - especially around threat detection, network behavior, or ICS/OT operations is a meaningful plus, but not a prerequisite.

Nice to Have:

  • Experience working with graph-based representations of network topology or asset relationships.
  • Familiarity with stream processing or event-driven architectures.
  • Exposure to containerized environments (Docker, Kubernetes) as a consumer/deployer, not necessarily an operator.

Compensation:

  • Salary: $225,000.00
  • Competitive Equity Package
  • Comprehensive Benefits Plan

#LI-JF1 #LI-REMOTE

#LI-NH1 #LI-REMOTE

Dragos is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, state, or local laws. All new hires must pass a background check as a condition of employment.