ZipRecruiter

Log In

1

Physics Based Machine Learning Jobs in Illinois (NOW HIRING)

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$127K - $167K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Advanced degree (MS or PhD) in EE, CS, Physics, or related field, or equivalent depth through ...

Paylocity

Machine Learning Engineer

Schaumburg, IL · On-site

Description: Paylocity is an award-winning provider of cloud-based HR and payroll software ... Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering ...

IMC Inc

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

Hardware Machine Learning Engineer Chicago, United States; New York, United States We are deploying ... Advanced degree (MS or PhD ) in EE, CS, Physics, or related field, or equivalent depth through ...

Darwill, Inc.

Machine Learning Engineer

Villa Park, IL · On-site

MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING) Overview Darwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Advanced degree (MS or PhD) in EE, CS, Physics, or related field, or equivalent depth through ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Advanced degree (MS or PhD) in EE, CS, Physics, or related field, or equivalent depth through ...

Gotion, Inc.

Machine Learning Engineer

Manteno, IL

This is a fully on-site role based in Manteno, IL focused on building innovative ML models from the ... Design and implement novel machine learning and deep learning models tailored to internal research ...

next page

Showing results 1-20

All JobsPhysics Based Machine Learning JobsPhysics Based Machine Learning Jobs in Illinois

Physics Based Machine Learning information

What types of projects or problems does a Physics Based Machine Learning professional typically work on?

Physics Based Machine Learning professionals often work on projects that involve applying machine learning techniques to physical systems, such as improving simulations in engineering, optimizing energy systems, or accelerating scientific research through data-driven modeling. Daily tasks might include developing algorithms that incorporate physical laws, analyzing simulation data, and collaborating with experts from engineering, data science, or research teams. The role can involve both theoretical and hands-on work, often requiring iterative testing and validation. This environment provides opportunities to tackle cutting-edge challenges, contribute to innovation, and potentially lead to career paths in research, product development, or advanced analytics.

What is a Physics Based Machine Learning job?

A Physics Based Machine Learning job involves developing machine learning models that incorporate physical laws and domain knowledge to improve predictions and interpretability. Professionals in this field work at the intersection of physics, data science, and artificial intelligence to create models that are more robust, generalizable, and efficient, especially in scientific and engineering applications. Responsibilities often include data analysis, algorithm development, numerical simulations, and integrating physics-based constraints into ML models. These roles are common in industries like climate science, robotics, materials science, and computational physics.

What are the key skills and qualifications needed to thrive in the Physics Based Machine Learning position, and why are they important?

To thrive in Physics Based Machine Learning, you need advanced knowledge of physics, strong programming skills (Python, MATLAB, or C++), and a deep understanding of machine learning and statistical modeling, typically supported by a master's or PhD in physics, engineering, or a related field. Familiarity with simulation software, scientific computing libraries (such as TensorFlow, PyTorch, NumPy), and version control systems is essential. Strong problem-solving ability, effective communication, and cross-disciplinary collaboration skills set outstanding candidates apart. These competencies are crucial for designing robust, real-world models that integrate physical principles with data-driven techniques to solve complex problems.

What are popular job titles related to Physics Based Machine Learning jobs in Illinois? For Physics Based Machine Learning jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Physics Based Machine Learning jobs in Illinois look for? The top searched job categories for Physics Based Machine Learning jobs in Illinois are:
What cities in Illinois are hiring for Physics Based Machine Learning jobs? Cities in Illinois with the most Physics Based Machine Learning job openings:
Physics Based Machine Learning jobs near you
Infographic showing various Physics Based Machine Learning job openings in Illinois as of June 2026, with employment types broken down into 94% Full Time, 5% Part Time, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Quantum Software Engineer - Machine Learning

Infleqtion

Chicago, IL • On-site

$100/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted yesterday

Job description

We are seeking a Quantum Software Engineer with expertise in quantum-inspired classical machine learning and quantum machine learning (QML). This role will focus on developing advanced ML models and algorithms that leverage tensor networks and related structured representations, supporting applications across quantum computing and quantum sensing platforms.
As a member of the Quantum Software division, you will work closely with teams spanning quantum computing and sensing hardware and algorithms to design scalable learning architectures that operate in hybrid classical-quantum workflows. The ideal candidate brings strong foundations in machine learning and mathematical physics, along with hands-on experience developing novel model architectures for structured, high-dimensional data.
This position offers the opportunity to contribute to next-generation ML techniques that bridge classical and quantum paradigms for real-world deployment.
Job Responsibilities
The duties and responsibilities outlined below include essential functions of the role. Depending on business needs, this role may perform a combination of some or all of the following duties. Duties, responsibilities, and activities may change, or new ones may be assigned:
  • Develop and implement quantum-inspired machine learning models, including tensor network-based architectures (e.g., MPS/TTN/PEPS-inspired models) for structured data analysis
  • Design and evaluate quantum machine learning algorithms suitable for near-term and fault-tolerant quantum computers
  • Build hybrid classical-quantum workflows integrating classical ML pipelines with quantum processors and/or quantum sensors
  • Develop ML models for signal processing, state estimation, calibration, and noise mitigation in quantum sensing systems
  • Collaborate with hardware and experimental teams to translate physical system characteristics into learning-based models
  • Optimize models for performance, scalability, and deployment in HPC and low-SWaP environments
  • Stay current with emerging research in tensor networks, quantum information science, and advanced ML architectures
  • Contribute to research publications, technical reports, and conference presentations
  • Provide technical mentorship and contribute to a collaborative, interdisciplinary research environment

Requirements
Required Qualifications
  • BS or MS in Computer Science, Physics, Applied Mathematics, Electrical Engineering, or a closely related field
  • Strong experience developing, training, and optimizing machine learning models
  • Demonstrated experience with tensor networks, structured linear algebra, or physics-informed ML architectures
  • Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX, TensorFlow)
  • Experience working in scientific computing and HPC environments leveraging GPU acceleration
  • Strong mathematical foundation in linear algebra, probability, and optimization
  • Ability to communicate complex theoretical and experimental concepts clearly across teams and to external customers
  • Demonstrated ability to work effectively in a collaborative, cross-functional, and fast-paced R&D environment
  • Resourceful problem-solver with a track record of delivering research ideas into prototype or production systems
  • Willingness to travel domestically and potentially internationally up to 10%

Preferred Qualifications
  • Ph.D. in Computer Science, Physics, Applied Mathematics, or a related field
  • Research experience in quantum machine learning and/or quantum information science
  • Experience implementing variational quantum algorithms, parameterized quantum circuits, or quantum kernel methods
  • Experience developing tensor network algorithms for large-scale modeling or simulation
  • Familiarity with quantum SDKs (e.g., Qiskit, Cirq, Braket, PennyLane)
  • Strong publication record in machine learning, quantum computing, or computational physics
  • Experience working with quantum sensor data or quantum hardware calibration workflows

Benefits
  • Salary range: $135,000 to $160,000
  • 100% company-paid medical, dental, vision, short/long-term disability
  • Employer-funded Health Savings Account
  • Unlimited PTO
  • 401(k) match
  • Company-paid Life and AD&D Insurance
  • Flexible Savings Account
  • Paid FMLA, Maternity/Paternity Leave
  • Employee Assistance Program
  • Student Loan Repayment
  • Equity Program

Apply