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Neural Engineer Jobs in Wisconsin (NOW HIRING)

Serve Robotics

$225K - $260K/yr

By optimizing distributed training pipelines, neural network architectures, and data processing ... Work closely with ML scientists and other engineers to integrate new models, experiments, and ...

University of Chicago Library

Staff Scientist

Institute, WI · On-site

$60K - $80K/yr

Minimal technical preferences include: expert level proficiency in programing (Python, C++), advanced proficiency in neural network model development, training, and validation, advanced proficiency ...

Next Gen Alloys

Data Scientist

Cudahy, WI

... and programming background. * Experience in deep learning, predictive modeling, data mining, and time series analysis. * Knowledge of image segmentation, generative models, convolutional neural ...

ATI

Data Scientist

Cudahy, WI · On-site

... and programming background. * Experience in deep learning, predictive modeling, data mining, and time series analysis. * Knowledge of image segmentation, generative models, convolutional neural ...

ATI

Data Scientist

Cudahy, WI

... and programming background. * Experience in deep learning, predictive modeling, data mining, and time series analysis. * Knowledge of image segmentation, generative models, convolutional neural ...

The Weather Channel

Senior Data Scientist

Madison, WI · On-site

Experience using/implementing non-parametric regression such as Neural Net, SVM, Random Forest ... Programming capabilities including C++, Java, Python is a plus but not necessary. Additional ...

Wisconsin

Research Specialist

Madison, WI

These experiments will test hypotheses about the neural bases of visual cognition in humans, with ... Additional duties may include programming experimental tasks and carrying out preprocessing and ...

Varsity Tutors

Machine Learning Tutor

Milwaukee, WI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... neural network architectures while preparing students for data science roles and advanced AI ...

Varsity Tutors

Machine Learning Tutor

Madison, WI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... neural network architectures while preparing students for data science roles and advanced AI ...

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All JobsNeural Engineer JobsNeural Engineer Jobs in Wisconsin

Neural Engineer information

See Wisconsin salary details

$60.1K

$112.7K

$204.9K

How much do neural engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for neural engineer in Wisconsin is $112,676.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,300.00 and $133,700.00 per year, depending on experience, location, and employer.

What jobs can you do with neural engineering?

Neural engineers can work in research and development roles focused on brain-computer interfaces, neural prosthetics, and neurotechnology devices. They often work in healthcare, biotech, or academic settings, applying skills in signal processing, neuroscience, and biomedical engineering to develop innovative solutions for neurological disorders and neural interface systems.

What does a neural engineer do?

A neural engineer designs and develops technologies to interface with the nervous system, such as brain-computer interfaces and neural prosthetics. They often work with biomedical signals, use tools like MATLAB or Python, and require knowledge of neuroscience, engineering, and programming. Their work supports medical treatments, research, and the development of neural devices.

What engineers make $300,000 a year?

Senior engineers in specialized fields such as software engineering, petroleum engineering, and aerospace engineering can earn $300,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High compensation often involves working in high-demand industries, holding managerial or executive positions, or possessing rare expertise and certifications.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, petroleum engineering, and aerospace engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High compensation often involves bonuses, stock options, or profit sharing, particularly in technology and energy sectors.

What types of projects and collaborations can a Neural Engineer expect to be involved in?

As a Neural Engineer, you may work on projects ranging from designing brain-computer interfaces and neural prosthetics to analyzing complex neural signals for clinical or research applications. Collaboration with neuroscientists, clinicians, software developers, and hardware engineers is common, ensuring a multidisciplinary approach to solving neurological challenges. Your daily responsibilities might include data analysis, prototyping, testing devices, and presenting findings to your team. This role offers opportunities to influence cutting-edge research and directly contribute to advancements in healthcare and neurotechnology.

What does a Neural Engineer do?

A Neural Engineer applies principles from neuroscience, engineering, and computer science to develop technologies that interface with the nervous system. This includes designing brain-computer interfaces, neuroprosthetics, and medical devices for treating neurological disorders. They work with signal processing, machine learning, and biomedical hardware to understand and manipulate neural activity. Their work has applications in healthcare, rehabilitation, and human augmentation.

What are the key skills and qualifications needed to thrive in the Neural Engineer position, and why are they important?

To thrive as a Neural Engineer, you need a strong background in biomedical engineering, neuroscience, and signal processing, often supported by an advanced degree in a related field. Proficiency with tools like MATLAB, Python, neural data acquisition systems, and familiarity with medical device regulations or certifications are commonly required. Problem-solving abilities, interdisciplinary teamwork, and effective communication set standout candidates apart. These skills and qualities are crucial for innovating and safely developing neural devices and technologies that bridge engineering and neuroscience.

What are the most commonly searched types of Neural Engineer jobs in Wisconsin? The most popular types of Neural Engineer jobs in Wisconsin are:
What are popular job titles related to Neural Engineer jobs in Wisconsin? For Neural Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Neural Engineer jobs in Wisconsin look for? The top searched job categories for Neural Engineer jobs in Wisconsin are:
What cities in Wisconsin are hiring for Neural Engineer jobs? Cities in Wisconsin with the most Neural Engineer job openings:
Neural Engineer jobs near you
Infographic showing various Neural Engineer job openings in Wisconsin as of July 2026, with employment types broken down into 91% Full Time, and 9% Part Time. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $112,676 per year, or $54.2 per hour.
Lead Machine Learning Engineer

Lead Machine Learning Engineer

Serve Robotics

On-site, Remote

$225K - $260K/yr

Full-time

Re-posted 19 days ago

Job description

At Serve Robotics, we're reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It's designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.
The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We're looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.
Who We Are
We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.
This role develops and scales large-scale machine learning training systems for multimodal robotics data, enabling the creation of high-performance autonomy models. By optimizing distributed training pipelines, neural network architectures, and data processing workflows, the position improves training efficiency, accelerates model iteration, and maximizes GPU utilization. The role collaborates closely with ML researchers and infrastructure teams, influencing the design, deployment, and performance of end-to-end autonomy models and the large-scale data pipelines that support them.
Responsibilities
  • Design and maintain training systems that can process and learn from petabyte-scale multimodal datasets (e.g., video and point cloud data). This includes ensuring data is efficiently loaded, distributed, and processed across large GPU clusters.
  • Identify and resolve bottlenecks in the training pipeline, including data loading, preprocessing, model computation, and inter-node communication, to maximize GPU utilization and reduce training time.
  • Work with the ML team to develop and refine neural network architectures suitable for autonomy tasks, particularly those handling high-dimensional and sequential sensor data.
  • Create and adjust loss functions and training strategies that help the model learn effectively from complex multimodal inputs and improve autonomy performance.
  • Configure, monitor, and maintain large-scale distributed training jobs across multiple machines and GPUs, ensuring stability, fault tolerance, and efficient resource usage.
  • Implement scalable systems to preprocess, transform, and augment large robotics datasets so that they are suitable for model training.
  • Work closely with ML scientists and other engineers to integrate new models, experiments, and training approaches into the production training pipeline.
  • Analyze training metrics, model outputs, and experiment logs to assess model performance and guide improvements in architecture, data usage, or training strategies.
  • Develop tools and workflows that allow teams to run experiments, track results, and iterate quickly on new model ideas or training approaches.

Qualifications
  • Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline.
  • Minimum of 5 years of professional experience developing, training, and deploying machine learning models in production environments.
  • Hands-on experience training machine learning models across multiple GPUs or compute nodes, including familiarity with distributed training frameworks and large dataset handling.
  • Strong programming skills in Python for implementing machine learning models, data pipelines, and training workflows.
  • Solid knowledge of core concepts such as neural networks, optimization algorithms, loss functions, model evaluation, and training methodologies.

What Makes You Stand out
  • Experience identifying and resolving training bottlenecks related to compute utilization, memory usage, and data throughput in machine learning systems.
  • Experience training machine learning models on robotics or autonomous driving datasets involving multimodal sensor inputs such as camera video, LiDAR point clouds, radar, or telemetry data.
  • Experience developing models that combine multiple data modalities (e.g., images, point clouds, and structured sensor data) into a unified learning system.
  • Peer-reviewed publications or significant research contributions in machine learning, robotics, or related areas.

*Please note: The listed base salary range applies to candidates based in the US. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely in Canada
  • Canada - ALL: $177k - $215k CAD

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