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Neural Engineering Jobs in Boston, MA (NOW HIRING)

Draft and prepare 339 Engineering Support cases for final review and approval by designated ... Artificial Intelligence/Neural Network software development and implementation Other Requirements:

Machine Learning Architect

Boston, MA · On-site

  • Medical

  • Dental

  • Vision

Work with hardware engineers to define and refine processor architecture based on insights learned ... Has built and trained neural networks from scratch * Deep knowledge of the structure and internal ...

AI Lead

Boston, MA · On-site

  • Medical

  • Dental

  • Vision

Work with hardware engineers to define and refine processor architecture based on insights learned ... Has built and trained neural networks from scratch * Deep knowledge of the structure and internal ...

Senior Data Scientist

Boston, MA · On-site

$109K - $190K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

You will work closely with product, engineering, operations, and business stakeholders to identify ... Practical knowledge of deep learning, neural networks, GenAI/LLM concepts, or AI system development.

Design Verification Engineer

Waltham, MA · On-site

$146K - $179K/yr

... of IP: - Neural Engine hardware - DRAM subsystem, memory controller logic - Encode and Decode ... programming skills with knowledge of data structures and algorithms Experience with Python, Perl ...

Senior Software Engineer, Next Gen Compute

Boston, MA · Hybrid

$133K - $175K/yr

... and neural networks that make our vehicles autonomous. The Next-Gen Technologies team is part of CORE. We work at the intersection of software engineering, machine learning, sensors, and hardware ...

Design Verification Engineer

Waltham, MA · On-site

$146K - $179K/yr

... of IP: - Neural Engine hardware - DRAM subsystem, memory controller logic - Encode and Decode ... programming skills with knowledge of data structures and algorithms Experience with Python, Perl ...

Firmware Engineer

Boston, MA · On-site

$110 - $170/hr

  • Medical

  • Retirement

  • PTO

... turn neural signals into meaningful product experiences. This is a hands-on role for someone who ... Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent ...

Senior Controls Systems Engineer - Ninja

Needham, MA · On-site

$115 - $130/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

You will collaborate with R&D, Product Development, and Advanced Engineering to ensure seamless ... neural networks, reinforcement learning, and supervised/unsupervised techniques for predictive ...

Showing results 41-60

Neural Engineering information

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How much do neural engineering jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for neural engineering in Boston, MA is $20.98, according to ZipRecruiter salary data. Most workers in this role earn between $17.50 and $22.74 per hour, depending on experience, location, and employer.

What is neural engineering?

Neural engineering is a multidisciplinary field that combines engineering, neuroscience, and computational approaches to understand, repair, enhance, or interface with the nervous system. Neural engineers develop devices such as brain-computer interfaces, neural prosthetics, and neurostimulation systems to restore or improve neural function. This field plays an important role in advancing treatments for neurological disorders and in creating technologies that bridge the gap between machines and the human brain.

What are the key skills and qualifications needed to thrive as a neural engineer, and why are they important?

To thrive as a Neural Engineer, you need a strong background in neuroscience, biomedical engineering, and signal processing, typically supported by an advanced degree in a related field. Familiarity with programming languages (such as MATLAB or Python), neuroimaging tools, and hardware platforms used for neural interfacing is essential. Excellent problem-solving skills, collaboration, and clear communication set standout professionals apart in this multidisciplinary environment. These skills are crucial for developing innovative neural technologies and translating research into effective clinical or commercial solutions.

Is neural engineering a good career?

Neural engineering is a growing interdisciplinary field that combines neuroscience, engineering, and computer science to develop technologies like brain-computer interfaces and neural prosthetics. It offers opportunities in research, healthcare, and industry, often requiring advanced degrees and technical skills. The field is expected to expand as neurotechnology advances and healthcare needs increase.

What can you do with a neural engineering degree?

A neural engineering degree prepares individuals for careers in developing brain-computer interfaces, neuroprosthetics, and neural signal processing. Graduates often work in research, healthcare, or technology companies, utilizing skills in neuroscience, engineering, and programming to innovate medical devices and neural systems.

What are jobs in neural engineering?

Jobs in neural engineering focus on helping research and design biomedical devices like prosthetic limbs and artificial organs. In these roles, you may determine the best way to implement designs for each situation, figure out the best way to link mechanical systems to the human brain, and find the most cost-effective ways to build devices. Neural engineering differs from engineering regular prosthetic limbs in that they receive instructions directly from the brain and often send information back, rather than simply being attached to the body. This often involves programming specialized software and figuring out how to make devices that can teach the brain how to use them. In recent years, neural engineering has started to move out of the medical realm, and there may be more jobs of that nature in the future. Neural engineering is a specific type of biomedical engineering, but should not be confused with jobs in the broader category.

What are some common interdisciplinary challenges faced by neural engineers when collaborating with clinicians and data scientists?

Neural engineers frequently work on teams that include clinicians, data scientists, and hardware specialists, which can present unique interdisciplinary challenges. Effective communication is essential, as team members often have different technical backgrounds and priorities—clinicians focus on patient outcomes, while data scientists emphasize analytical accuracy. Bridging the gap between clinical needs and technical feasibility requires adaptability, openness to feedback, and a willingness to learn new concepts. Building strong collaborative relationships and participating in regular cross-functional meetings can help ensure that project goals are clearly understood and met by all stakeholders.

What are the most commonly searched types of Neural Engineering jobs in Boston, MA?

The most popular types of Neural Engineering jobs in Boston, MA are:

What are popular job titles related to Neural Engineering jobs in Boston, MA?

For Neural Engineering jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Neural Engineering jobs in Boston, MA look for?

The top searched job categories for Neural Engineering jobs in Boston, MA are:

What cities near Boston, MA are hiring for Neural Engineering jobs?

Cities near Boston, MA with the most Neural Engineering job openings:

Infographic showing various Neural Engineering job openings in Boston, MA as of August 2026, with employment types broken down into 5% Internship, 77% Full Time, and 18% Contract. Highlights an 93% In-person, and 7% Hybrid job distribution, with an average salary of $43,645 per year, or $21 per hour.

Staff Machine Learning Engineer, Technical Lead

Paperless Parts

Boston, MA • On-site

Full-time

Re-posted 9 days ago


Job description

Job Summary:
Paperless Parts is a SaaS startup helping manufacturers quote faster and win more work. They are seeking a Staff Machine Learning Engineer, Technical Lead to drive R&D execution and lead the technical efforts in building the core manufacturing intelligence engine. This role involves mentoring early-career engineers and operationalizing machine learning infrastructure to solve complex manufacturing challenges.
Responsibilities:
• Drive R&D Execution: Own planning and execution of the AI/ML pod’s backlog. Partner closely with the Chief Scientist and other engineering pods to ensure the research pipeline aligns smoothly with border product timelines.
• Prototype and Transition: Lead the hands-on prototyping of novel solutions and transition of successful proofs-of-concept into production-ready services. Guide the strategic migration of workloads, identifying opportunities to shift repetitive tasks from expensive frontier models to fine-tuned, open-source architectures.
• Operationalize ML Infrastructure: Develop scalable, repeatable approaches to labeling data, training models, and deploying services that support our products with AI capabilities.
• Design Rigorous Benchmarks: Define and track metrics that evaluate the effectiveness and costs of our AI-powered solutions, enabling key technology decisions to be data-driven.
• Mentor the Pod: Act as the technical anchor and primary mentor for early-career ML engineers. Cultivate an engineering culture of deep theoretical and practical rigor through hands-on pairing and comprehensive design and code reviews.
Qualifications:
Required:
• 8+ years of experience in relevant R&D roles with a strong background in SaaS products at scale
• Advanced Academic Foundation: a technical degree in Computer Science, Applied Mathematics, or closely related field, with a strong understanding of the mathematics behind modern AI/ML techniques is essential.
• AI/ML Fundamentals: A robust understanding of core machine learning and deep learning theory, including neural networks, statistical modeling and inference, and metric learning.
• MLOps: Experience working with cloud-native patterns for ML pipelines, including platforms like AWS SageMaker.
• Communication Mastery: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and influence decisions without relying on authority.
Preferred:
• start-up to scale-up transition experience preferred
• An advanced degree and track record of peer-reviewed publications is a strong plus when paired with proven software experience in industry.
Company:
Paperless Parts is a manufacturing intelligence company building a new type of marketplace for custom parts. Founded in 2017, the company is headquartered in Boston, USA, with a team of 51-200 employees. The company is currently Growth Stage.