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Neural Signal Processing Jobs in Detroit, MI (NOW HIRING)

Canopy

Senior Machine Learning Engineer

Detroit, MI · Remote

$126K - $180K/yr

Stay ahead of industry advancements in machine learning, AI sensing, and signal processing ... White-box understanding of classical ML algorithms (SVMs, HMMs, Decision Trees) and modern neural ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

Stay ahead of industry advancements in machine learning, AI sensing, and signal processing ... White-box understanding of classical ML algorithms (SVMs, HMMs, Decision Trees) and modern neural ...

All JobsNeural Signal Processing JobsNeural Signal Processing Jobs in Detroit, MI

Neural Signal Processing information

See Detroit, MI salary details

$53K

$130K

$191.6K

How much do neural signal processing jobs pay per year?

As of Aug 21, 2026, the average yearly pay for neural signal processing in Detroit, MI is $130,031.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,400.00 and $146,000.00 per year, depending on experience, location, and employer.

What is neural signal processing?

Neural signal processing is the analysis and interpretation of electrical signals generated by neurons in the brain or nervous system. This field combines neuroscience, engineering, and computer science to develop methods and algorithms that can decode, filter, and make sense of complex neural data. Applications include brain-computer interfaces, medical diagnostics, and research into how the brain functions. Neural signal processing is critical for advancing our understanding of neural circuits and developing new treatments for neurological disorders.

What are the key skills and qualifications needed to thrive as a neural signal processing specialist?

To thrive in Neural Signal Processing, you need a solid background in neuroscience, signal processing, and programming, often supported by an advanced degree in biomedical engineering, neuroscience, or related fields. Familiarity with tools like MATLAB, Python, EEG/MEG analysis software, and machine learning frameworks is typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret complex data and collaborate with interdisciplinary teams. These skills ensure accurate data analysis, advancement of brain-computer interfaces, and successful contributions to neuroscience research.

What are some common challenges faced by professionals in neural signal processing roles, and how can they be addressed?

Professionals in neural signal processing often face challenges such as managing noisy or artifact-laden data, ensuring real-time processing capabilities, and integrating signals from multiple modalities (e.g., EEG, fMRI). Addressing these challenges typically involves staying updated on advanced filtering techniques, collaborating closely with neuroscientists and engineers, and leveraging robust software tools for data analysis. Continuous learning and teamwork are essential, as projects often require interdisciplinary cooperation and adaptation to evolving research protocols.

What is the difference between Neural Signal Processing vs Neural Data Analyst?

AspectNeural Signal ProcessingNeural Data Analyst
Required CredentialsBackground in neuroscience, signal processing, programming (Python, MATLAB)Statistics, data analysis, programming (Python, R)
Work EnvironmentResearch labs, healthcare, neurotechnology companiesData-focused roles in research institutions, healthcare, biotech
Industry UsageDesigning algorithms for neural signals, signal decodingAnalyzing neural data sets, interpreting results

Neural Signal Processing involves developing algorithms to analyze and interpret neural signals, often requiring expertise in signal processing and neuroscience. Neural Data Analysts focus on examining neural data sets to extract insights, emphasizing statistical analysis and data interpretation. While both roles work with neural data, Neural Signal Processing is more technical and algorithm-driven, whereas Neural Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Neural Signal Processing jobs in Detroit, MI?

For Neural Signal Processing jobs in Detroit, MI, the most frequently searched job titles are:

What job categories do people searching Neural Signal Processing jobs in Detroit, MI look for?

The top searched job categories for Neural Signal Processing jobs in Detroit, MI are:

What cities near Detroit, MI are hiring for Neural Signal Processing jobs?

Cities near Detroit, MI with the most Neural Signal Processing job openings:

Neural Signal Processing jobs near you
Infographic showing various Neural Signal Processing job openings in Detroit, MI as of June 2026, with employment types broken down into 7% As Needed, 76% Full Time, 11% Part Time, and 6% Nights. Highlights an 69% Physical, 3% Hybrid, and 28% Remote job distribution, with an average salary of $130,031 per year, or $62.5 per hour.

Research Engineer - Prognostics & Applied Data Science

HTC Global Services

Dearborn, MI • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago

Job description

Job Title
Research Engineer - Prognostics & Applied Data Science
Overview
We are seeking a Research Engineer with expertise in applied data science, machine learning, and predictive modeling to develop advanced prognostic features for connected vehicle systems. This role focuses on building predictive models, processing large-scale vehicle data, and developing algorithms that support diagnostics, fault detection, and remaining useful life estimation for vehicle components.
This is a hybrid position requiring four days per week onsite.
Key Responsibilities
  • Develop prognostic features from concept through production deployment.
  • Build physics-informed machine learning models that combine first-principles physics with machine learning techniques.
  • Design prognostics and Remaining Useful Life (RUL) models for vehicle subsystems.
  • Convert predictive models into optimized C++ code for embedded vehicle systems.
  • Develop digital signal processing pipelines and time-series analytics for multi-sensor vehicle data.
  • Design and validate fault detection and isolation (FDI) algorithms.
  • Apply statistical methods including causal inference, multivariate analysis, ANOVA, principal component analysis (PCA), clustering, neural networks, and Gaussian regression.
  • Support the complete development lifecycle from modeling and simulation through hardware validation and production deployment.
  • Collaborate with subject matter experts to develop diagnostics and prognostic algorithms for vehicle components and systems.
  • Process and analyze large-scale telemetry data using Python, SQL, Spark, Hadoop, and cloud platforms.
  • Utilize MATLAB, Simulink, and calibration tools to develop and optimize predictive algorithms.
  • Work cross-functionally to support successful implementation of production software.

Required Qualifications
  • Master's degree in Mechanical Engineering, Electrical Engineering, Computer Science, Computer Engineering, Physics, Mathematics, or a related field, or an equivalent combination of education and experience.
  • 4+ years of experience applying statistical methods such as ANOVA, PCA, correspondence analysis, clustering, factor analysis, multivariate analysis, neural networks, causal inference, and Gaussian regression.
  • 3+ years of experience with Python and SQL.
  • Experience with C++ programming.
  • Experience with data science methodologies and cloud-based data platforms.
  • Experience with embedded controls, onboard diagnostics, sensor processing, and physics-based modeling.
  • Experience using numerical modeling and simulation tools such as MATLAB and Simulink.
  • Experience with digital signal processing (DSP), data structures, algorithms, and software engineering principles.
  • Strong analytical, communication, interpersonal, and problem-solving skills.
  • Self-motivated with the ability to work in cross-functional teams.

Preferred Qualifications
  • PhD in Mechanical Engineering, Electrical Engineering, Computer Science, Computer Engineering, Physics, Mathematics, or a related field.
  • Experience in dynamic systems, controls, robotics, or prognostics and health management.
  • Experience developing automotive prognostics using connected vehicle data.
  • Experience applying machine learning methods including time-series forecasting, random forests, clustering, and neural networks.
  • Experience with Python, R, Spark, and Hadoop.
  • Experience developing embedded automotive software using MATLAB and C++.
  • Familiarity with ATI and ETAS calibration tools.
  • Excellent verbal and written communication skills.

What Makes HTC A Great Place To Build Your Future
HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you'll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You'll have long-term opportunities to grow your career and develop skills in the latest emerging technologies.
At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks.
Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.
#LI-Hybrid #LI-CP1

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