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Mid Level Neuromorphic Computing Jobs in Michigan

Stellantis

Machine Learning Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

This role will leverage curated datasets to build a customer-level preference simulation engine ... This is a highly impactful role for an early-to-mid career data scientist who enjoys combining ...

Stellantis

Machine Learning Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

This is a highly impactful role for an early-to-mid career data scientist who enjoys combining ... Feature-level willingness-to-pay data * Customer preference models * Translate model outputs into ...

SPX

... level of customer service. * Provision and maintain all end-user computing equipment, such as ... Provide constructive feedback and coaching to team members; participate in mid-year and annual ...

Brooksource

Mechanical Engineer

Novi, MI · On-site

$45 - $65/hr

... for Senior level) * Experience designing components such as castings, stampings, extrusions ... Familiarity with low- to mid-volume manufacturing processes * Ability to interpret structural and ...

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All JobsMid Level Neuromorphic Computing JobsMid Level Neuromorphic Computing Jobs in Michigan

Mid Level Neuromorphic Computing information

What is a mid level neuromorphic computing professional?

Mid level neuromorphic computing professionals are specialists with several years of experience who design, develop, and optimize hardware and software systems inspired by the structure and function of the human brain. They typically work on building and programming neuromorphic chips, developing algorithms that mimic neural processes, and integrating these systems into real-world applications such as robotics or edge computing. Their expertise bridges neuroscience, computer engineering, and artificial intelligence, and they often collaborate with interdisciplinary teams to advance brain-inspired computing technologies.

What are the key skills and qualifications needed to thrive as a mid level neuromorphic computing engineer?

To thrive as a Mid Level Neuromorphic Computing Engineer, you need a solid background in computer engineering, neuroscience, and machine learning, usually supported by a relevant degree and experience with neural network architectures. Familiarity with tools like Python, MATLAB, TensorFlow, and simulation platforms such as NEST or SpiNNaker, along with knowledge of specialized hardware, is typically required. Strong problem-solving, collaboration, and communication skills help you innovate and effectively share complex ideas with multidisciplinary teams. These skills and qualifications are crucial for developing advanced neuromorphic systems that bridge neuroscience and AI, pushing the boundaries of efficient computing.

What are some common challenges faced by professionals in mid level neuromorphic computing roles, and how can they be addressed?

Professionals in mid-level neuromorphic computing roles often encounter challenges such as integrating novel hardware with existing software systems, managing the complexity of neural-inspired algorithms, and keeping pace with rapid advancements in the field. Collaborating closely with multidisciplinary teams—including hardware engineers, data scientists, and neuroscientists—can help address these challenges. Additionally, staying updated on the latest research and industry trends, as well as participating in collaborative projects, can enhance problem-solving skills and foster innovation in this evolving area.

What is the difference between Mid Level Neuromorphic Computing vs Mid Level Machine Learning Engineer?

AspectMid Level Neuromorphic ComputingMid Level Machine Learning Engineer
Required CredentialsBachelor's in Computer Science, Electrical Engineering, or related field; knowledge of neuromorphic hardwareBachelor's in Computer Science, Data Science, or related; experience with ML frameworks
Work EnvironmentResearch labs, hardware development, AI hardware companiesTech companies, startups, data-driven organizations
Industry UsageAI hardware, neuromorphic chip design, cognitive computingSoftware development, AI applications, data analysis

Mid Level Neuromorphic Computing professionals focus on hardware and cognitive architectures inspired by the brain, often working with specialized hardware and research teams. In contrast, Mid Level Machine Learning Engineers develop algorithms and models primarily in software to solve data-driven problems. Both roles require a strong technical background but differ in their focus on hardware versus software applications.

What are popular job titles related to Mid Level Neuromorphic Computing jobs in Michigan?

For Mid Level Neuromorphic Computing jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Mid Level Neuromorphic Computing jobs in Michigan look for?

The top searched job categories for Mid Level Neuromorphic Computing jobs in Michigan are:

What cities in Michigan are hiring for Mid Level Neuromorphic Computing jobs?

Cities in Michigan with the most Mid Level Neuromorphic Computing job openings:

Mid Level Neuromorphic Computing jobs near you
Infographic showing various Mid Level Neuromorphic Computing job openings in Michigan as of August 2026, with employment types broken down into 65% Full Time, and 35% Contract. Highlights an 100% In-person job distribution.

Machine Learning Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Posted 29 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

15th of 45 rated automakers

Job description

We are looking for a Machine Learning Engineer / Data Scientist to develop advanced statistical models and simulations that drive Vehicle Configuration Optimization (VCO). This role will leverage curated datasets to build a customer-level preference simulation engine, enabling optimized vehicle order guides (VOGs) for future model years.
This is a highly impactful role for an early-to-mid career data scientist who enjoys combining statistical rigor, large-scale data, and real-world business impact.
Key Responsibilities:
  • Build and run large-scale simulations (e.g., 50,000 synthetic customers) to model vehicle purchase behavior
  • Develop statistical and machine learning models using Databricks
  • Leverage datasets including:
    • Historical vehicle sales
    • Competitive sales data
    • Feature-level willingness-to-pay data
    • Customer preference models
  • Translate model outputs into optimized Vehicle Order Guides (VOGs) that inform product configuration decisions
  • Perform exploratory data analysis and feature engineering on complex datasets
  • Collaborate closely with Data Engineering to refine and leverage curated datasets
  • Communicate insights and model recommendations to business stakeholders
  • Continuously evaluate and improve model accuracy and assumptions

Basic Qualifications:
  • Bachelors Degree Required
  • Minimum 5 years of experience in data science, machine learning, or applied statistics
  • Strong experience with Databricks (critical requirement)
  • Proficiency in Python (Pandas, NumPy, scikit-learn, PySpark)
  • Strong SQL skills
  • Solid background in statistical modeling, simulation techniques, and experimental design
  • Experience translating analytical results into business decisions

Preferred Qualifications:
  • Experience with choice modeling, conjoint analysis, or demand modeling
  • Background in automotive, pricing, or product optimization analytics
  • Experience working with large-scale simulation frameworks
  • Familiarity with Spark and distributed computing
  • Exposure to MLOps or model productionization

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