Machine Learning Engineer
Description For Machine Learning Engineer
Eriez, a global leader in separation technologies with over 80 years of experience, is seeking a Machine Learning Engineer to join their Research and Development team. The ideal candidate will conduct research and development of innovative signal processing and machine learning algorithms for real-time sensing and detection systems across various industries. This role offers the opportunity to work on cutting-edge technologies, collaborate with university partners, and contribute to the development of sophisticated algorithms for industrial-grade sensors and detection systems. The position requires a strong background in machine learning, deep learning, and signal processing, with a focus on physics-informed neural networks and domain-enriched deep learning. Join a company committed to excellence and innovation, with a global presence and a dedicated workforce of over 900 employees.
Responsibilities For Machine Learning Engineer
- Research and develop novel algorithmic solutions in key areas of separation technologies
- Design and optimize algorithms to extract small-amplitude signals of interest in large-amplitude noisy environments
- Utilize CI/CD strategies based on industry-standard MLOps principles
- Convert developed algorithms to high-level language (such as C++) and work into real-time system
- Collect and analyze data from laboratory equipment using tools like Python/MATLAB
- Work closely with other R&D engineers and scientists to evaluate and develop new technologies
- Aid in grant proposal writing to secure funding opportunities
- Collaborate with university partners on fundamental research work
- Develop documentation for various stakeholders
Requirements For Machine Learning Engineer
- Master of Science degree in 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
- 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 (PyTorch, TensorFlow, Keras, etc.)
- Familiarity with Linux, Visual Studio Code, Azure DevOps, MLflow, Git
- Excellent communication skills (written and verbal)
Benefits For Machine Learning Engineer
- 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
