ZipRecruiter

Log In

1

Neural Engineering Jobs in Philadelphia, PA (NOW HIRING)

Redolent, Inc.

US_East | Data Engineer_L3

Philadelphia, PA · On-site

$115K - $138K/yr

Apply deep learning and neural network techniques for customer classification and profiling ... Data Engineering & Pipelines • Work with data engineers to design and develop robust data ...

Forhyre

Prompt Engineers

Philadelphia, PA · On-site

Strong understanding of AI models, algorithms, and neural networks. * Experience in prompt engineering, creative writing, or content creation is a plus. * Proficiency in programming languages such as ...

Programmers.io

Big Data Engineer

Pennington, NJ · On-site

$56.25 - $74.50/hr

Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Knowledge of advanced ...

asrcfh

Senior Data Analyst

Moorestown, NJ · On-site

$84K - $107K/yr

ASRC Federal Mission Solutions is a premier provider of systems engineering, software engineering ... Training deep neural networks including MLPs, CNNs, Transformers, and others as required * Working ...

asrcfh

Senior Data Analyst

Moorestown, NJ

$84K - $107K/yr

ASRC Federal Mission Solutions is a premier provider of systems engineering, software engineering ... Training deep neural networks including MLPs, CNNs, Transformers, and others as required * Working ...

next page

Showing results 1-20

All JobsNeural Engineering JobsNeural Engineering Jobs in Philadelphia, PA

Neural Engineering information

See Philadelphia, PA salary details

$10

$18

$28

How much do neural engineering jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for neural engineering in Philadelphia, PA is $18.46, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $20.00 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.
More about Neural Engineering jobs
What are popular job titles related to Neural Engineering jobs in Philadelphia, PA? For Neural Engineering jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Neural Engineering jobs in Philadelphia, PA look for? The top searched job categories for Neural Engineering jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Neural Engineering jobs? Cities near Philadelphia, PA with the most Neural Engineering job openings:
Neural Engineering jobs near you
Infographic showing various Neural Engineering job openings in Philadelphia, PA as of August 2026, with employment types broken down into 5% Internship, 78% Full Time, and 17% Contract. Highlights an 94% In-person, and 6% Hybrid job distribution, with an average salary of $38,396 per year, or $18.5 per hour.

GPU Performance Engineer | Experienced Hire

SIG Susquehanna

Bala Cynwyd, PA • On-site

$120 - $160/hr

Other

Posted 2 days ago

New

Job description

Overview

We are looking for a GPU Performance Engineer to build highly optimized CUDA kernels for low-latency inference. This role focuses on workloads where off-the-shelf runtimes and vendor libraries do not fully exploit the structure of the model, and where custom kernels, memory layouts, and execution strategies can deliver meaningful gains.

You will work closely with quantitative researchers and engineers to understand model structure, identify computational bottlenecks, and convert mathematical ideas into production-grade GPU implementations. Using your understanding of GPU hardware, you will help shape models that are both mathematically effective and efficient to run. The problems span compact neural networks, tree-based models, and other structured inference workloads where latency, throughput, and efficiency all matter.

This role is a strong fit for someone who enjoys low-level optimization, performance analysis, and translating abstract models into hardware-efficient code.

What you’ll do
  • Design, implement, and optimize custom CUDA kernels for latency-critical inference workloads
  • Develop fine-grained GPU implementations tailored to specific model structures
  • Analyze quantitative research models and computational bottlenecks to identify opportunities for parallelization and hardware-efficient execution
  • Collaborate directly with quantitative researchers to translate mathematical models into high-performance computing pipelines
  • Optimize end-to-end inference performance through kernel tuning, memory‑layout design, execution strategy, I/O optimization, and precision tradeoffs
  • Profile and benchmark GPU performance
  • Improve latency and throughput in production inference systems
  • Contribute to GPU architecture decisions and performance best practices
What we’re looking for
  • Strong proficiency in writing and optimizing CUDA kernels
  • Solid programming experience in C/C++ (preferred)
  • Deep understanding of GPU architecture, including memory hierarchy, SIMT execution, occupancy, and latency/throughput tradeoffs
  • Ability to reason about numerical stability, precision, performance tradeoffs, and how model design choices affect hardware efficiency
  • Strong problem‑solving skills and comfort working with low-level systems
Preferred qualifications
  • PhD in mathematics, physics, computer science, engineering, or a related quantitative field
  • Strong background in linear algebra, probability, numerical methods, or scientific computing
  • Experience working with quantitative research teams or financial models
  • Demonstrated ability to improve real-world inference performance beyond baseline framework or library implementations
  • Familiarity with PTX-level behavior, tensor‑core utilization, or architecture-specific tuning
  • Exposure to ONNX Runtime, TensorRT, Triton, TVM, or similar systems
  • Exposure to neural networks, tree-based models (e.g., LightGBM), state‑space models (e.g., Mamba architectures), and experience with kernel fusion, custom operators, model compilation, or graph-level optimization
#J-18808-Ljbffr

Apply