Machine Learning Engineer

About Us:

Eriez is a global leader in separation technologies, providing innovative solutions across various industries for over 80 years. Our commitment to excellence and cutting-edge technology has made us a trusted partner in the mining, food, recycling, and other process industries. With a dedicated workforce of over 900 employees and a strong global presence, we focus on delivering highly effective separation and detection solutions designed to enhance productivity and reduce operational costs.

About the Role:

We are seeking a Machine Learning Engineer to join our Research and development team. The ideal candidate will conduct research and development of innovative signal processing and machine learning (ML) algorithms that will drive the development of modern real-time sensing and detection systems in a variety of applications. In this role, you will be leading efforts in developing sophisticated algorithms for real-time industrial grade sensors/detection systems using traditional digital signal processing, machine learning, and deep learning principles, along with pattern recognition, filtering, and other modern data analysis techniques

Responsibilities:

• Research and develop novel algorithmic solutions in key areas of separation technologies for mining, food, recycling, packaging, aggregate and other processing industries.
• Design and optimize algorithms to extract small-amplitude signals of interest in large-amplitude noisy environments in various sensing and detection equipment.
• Utilize continuous integration/development (CI/CD) strategies based on industrystandard MLOps principles to develop and release production ready algorithms.
• Convert developed algorithms to high-level language (such as C++) and work into real-time system.
• Collect data from laboratory equipment and analyze data sets using tools like Python/MATLAB.
• Work closely with other R&D engineers and scientists to evaluate and develop new technologies to help expand and enhance current product offerings.
• Aid in grant proposal writing to secure funding opportunities in support of the R&D organization programs.
• Collaborate with university partners on fundamental research work at the intersection of electromagnetic sensing and algorithm development.
• Develop documentation for use by engineering, sales, manufacturing, government, suppliers, and customers.
• Perform other similar and related duties as assigned by the immediate supervisor.

Requirements

• Minimum of a Master of Science degree in either Electrical Engineering, Computer Science, or Software Engineering with a specialization in Domain. Enriched Deep Learning and Physics-Informed Neural Networks.
• Minimum 2 years of research experience in designing, troubleshooting, and testing of machine learning and deep learning algorithms, with a focus on building physics-informed learnable denoisers.
• Solid understanding of Probability, Statistics, Linear Algebra, Signal Processing, Filter Design, and Convex Optimization.
• Proficient in Python, C++, MATLAB or similar high-level programming and scripting languages.
• Proficient in ML frameworks and libraries, such as PyTorch, TensorFlow, Keras, Torchdiffeq, Sci-kit Learn, NumPy, Pandas, SciPy, Matplotlib, CuDNN, OpenCV.
• Familiarity with Linux, Visual Studio Code, Azure DevOps, MLflow, Git.
• Possess a Ph.D. in Electrical Engineering, Computer Science, or Software Engineering.
• Possess the hands-on ability to collect meaningful data from prototype equipment for algorithm evaluation, including the ability to interface with electronic hardware.
• Possess the ability to lead a research and development project from inception to completion.
• Possess excellent communication skills (written and verbal).
• Experience programming in either C or C# is highly desirable.

Benefits

• 401(k)
• Employer 401(k) matching
• Dental insurance
• Disability insurance
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid time off
• Tuition reimbursement
• Vision Insurance

• *****Compensation commensurate with experience ****