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Kalman Filter Estimation Jobs in Michigan (NOW HIRING)

Kalman Filter Estimation information

What is Kalman filter estimation?

Kalman Filter Estimation is a mathematical algorithm used to estimate the state of a dynamic system from a series of noisy measurements. It is widely applied in fields such as robotics, aerospace, and navigation to provide real-time, optimal estimates of unknown variables by combining predictions from a model with observed data. The filter works recursively, meaning it updates its estimates and uncertainties as new measurements become available. Its strength lies in efficiently handling uncertainties and noise in both the system model and the measurements.

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

To excel as a Kalman Filter Estimation Engineer, you need a strong background in control theory, linear algebra, statistics, and typically a degree in electrical engineering, robotics, or applied mathematics. Familiarity with MATLAB, Python, C++, and simulation tools like Simulink, as well as experience implementing Kalman filters in real-time systems, is highly valued. Analytical thinking, problem-solving, and effective communication are important soft skills for collaborating with multidisciplinary teams and presenting complex results. These competencies ensure accurate state estimation and system reliability in applications such as navigation, robotics, and sensor fusion.

What are some common challenges faced by professionals working in Kalman filter estimation, and how can they be addressed?

Professionals working in Kalman Filter Estimation often encounter challenges such as model inaccuracies, noisy sensor data, and computational limitations, especially in real-time applications. Addressing these issues typically involves rigorous sensor calibration, careful tuning of filter parameters, and choosing appropriate variants of the Kalman filter, such as the Extended or Unscented Kalman Filter for nonlinear systems. Collaboration with domain experts and regular validation against ground truth data also help ensure robust performance. Additionally, staying updated with the latest research and tools in estimation theory can provide innovative solutions to emerging challenges.

What is the difference between Kalman Filter Estimation vs Signal Processing Engineer?

AspectKalman Filter EstimationSignal Processing Engineer
CredentialsMathematics, control systems, engineering degreesElectrical engineering, computer science, or related fields
Work EnvironmentResearch labs, aerospace, robotics, automationCommunications, audio/video, telecommunications industries
Industry UsageNavigation, robotics, sensor fusionFiltering, data analysis, signal enhancement

Kalman Filter Estimation focuses on estimating the state of dynamic systems using mathematical models, often in robotics and navigation. Signal Processing Engineers design and implement algorithms to analyze and modify signals in various industries. While both roles involve data analysis and mathematical skills, Kalman Filter Estimation is specialized in state estimation for control systems, whereas Signal Processing Engineers work broadly on signal manipulation and enhancement.

What cities in Michigan are hiring for Kalman Filter Estimation jobs?

Cities in Michigan with the most Kalman Filter Estimation job openings:

Senior Software Engineer - Battery State Estimation

General Motors

Milford, MI • On-site

$107K - $142K/yr

Full-time

Posted 18 days ago


General Motors rating

8.2

Company rating: 8.2 out of 10

General Motors

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7.4

Company rating compared to similar companies: 7.4 out of 10

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Based on 6,288 frontline employees who took The Breakroom Quiz


Job description

Job Description
Work Classification:
Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to the Milford Proving Ground in Milford, MI three times per week, at minimum.
The Role:
General Motors is undergoing a major transformation in how we design vehicles, deliver customer value, and scale electric mobility. As we move toward a fully Software-Defined Vehicle (SDV) architecture, core battery software capabilities such as Battery State Estimation have become foundational to safety, performance, and customer trust. Our Battery & High Voltage Software organization is at the forefront of this transformation, developing production-grade software that powers millions of vehicles and continues improving through data-driven insights and over-the-air updates.
We are currently seeking experienced and highly motivated candidates for the role of Senior Software Engineer - Battery State Estimation. This role is responsible for the design, implementation, verification, and lifecycle evolution of State-of-Charge (SOC), State-of-Health (SOH), and State-of-Power (SOP) estimation algorithms for GM's next-generation high-voltage battery platforms. The position requires deep technical ownership across algorithm development, embedded software implementation, and system-level validation in virtual and physical environments. This role is ideal for engineers who have delivered estimation algorithms into production vehicles and are ready to lead within an SDV, virtual-validation-first development model.
In this position, you will own outcomes end-to-end-from concept through production deployment and continuous improvement. You will be empowered to shape technical direction, influence development processes, and raise the quality bar across estimation software by leveraging model-based design, early virtualization, and automation. Your work will directly impact range accuracy, fast-charge behavior, battery longevity, safety margins, and vehicle performance-attributes that define the EV customer experience and GM's competitiveness in the market.
What You'll Do:
  • Design, develop, and productionize robust battery state estimation algorithms for SOC, SOH, and SOP using physics-based, model-based, and hybrid data-driven estimation techniques.
  • Develop observers and filters (e.g., equivalent-circuit and electrochemical-informed models, Kalman-filter-based approaches) that remain accurate across temperature extremes, power transients, sensor noise, and battery aging.
  • Incorporate calendar and cycle aging effects into estimation logic so outputs remain truthful throughout the battery lifecycle and across chemistries and pack architectures.
  • Implement estimation algorithms as production-quality embedded software in C/C++, meeting GM standards for safety, cybersecurity, and coding discipline, including MISRA compliance.
  • Architect software with a focus on modularity, portability, and hardware abstraction, enabling reuse across multiple vehicle programs and evolving E/E architectures.
  • Define and advocate calibration strategies and model-based approaches that reduce complexity while improving robustness and long-term maintainability.
  • Lead shift-left verification, technical root-cause analysis and validation through MIL, SIL, and HIL test environments to enable early defect discovery and high validation coverage.
  • Develop automated regression, robustness, and fault-injection test suites integrated into CI pipelines to enforce built-in quality throughout development.
  • Collaborate cross-functionally with Cell and Pack Engineering, Systems & Functional Safety, Validation, Calibration, Vehicle Performance, SDV Platform and Research & Development teams.
  • Mentor and guide other engineers, contribute to technical planning events, and help evolve GM's battery estimation architecture as a scalable SDV service.
  • Own deliverables end-to-end and continuously improving technical rigor, development efficiency, and software quality.

Your Skills & Abilities (Required Qualifications):
  • Bachelor's degree in Electrical, Mechanical, Chemical, or Computer Engineering, or Computer Science.
  • Minimum 5 years of experience delivering embedded software for high-voltage battery systems or similar complex engineering systems.
  • Strong proficiency in C/C++ for embedded systems development.
  • Demonstrated hands-on production experience with SOC, SOH, and/or SOP estimation algorithms deployed in vehicles.
  • Strong proficiency in MATLAB/Simulink and Python, with hands-on experience in modeling, analysis, automation, and Model-Based Development (MBD) workflows.
  • Demonstrated success executing software and controls feature verification in MIL, SIL, and HIL environments.
  • Experience working in Agile/Scrum environments and cross-functional automotive programs.
  • Proven ability to operate effectively in ambiguous, fast-paced SDV development contexts with strong technical ownership and accountability.
  • Proven experience leveraging Battery Data to generate actionable insights that improve battery performance, reliability, and lifecycle characteristics.

What Will Give You a Competitive Edge (Preferred Qualifications):
  • Master's or PhD degree in Engineering or Computer Science.
  • Deep expertise in battery modeling and estimation techniques, including observer design and Kalman filter-based approaches.
  • 8+ years of experience delivering embedded software for high-voltage battery systems or similar complex engineering systems.
  • Hands-on experience with battery cell characterization, pack testing, and lab-based validation.
  • Familiarity with lithium-ion chemistries such as LFP and high-nickel NMC/LMR and associated aging mechanisms.
  • Experience with ETAS INCA, MDA, or similar calibration and measurement tools.
  • Experience working within Software-Defined Vehicle (SDV) architectures and CI/CD-based software delivery pipelines.
This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.This job may be eligible for relocation benefits.
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
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General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
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About General Motors

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General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908