**This position is for our Pittsburgh, PA office - only apply if you are based there or willing to relocate**
At TDK Qeexo, we are transforming the utilization and interaction with sensor data. As pioneers in automating end-to-end machine learning for edge devices, we are reshaping the landscape of "tinyML" development. Collaborating with leading global companies, we empower teams to effortlessly devise and implement machine learning solutions for industrial applications, all without the need for coding. Originating as a spin-off from Carnegie Mellon University in 2012, we are now a proud part of TDK Corporation, a prominent global player in sensor technology.
We are looking for a machine learning expert who loves working with sensor data, loves developing novel algorithms, is not afraid of challenging, open-ended problems, and wants to help us shape the future of lightweight machine learning. You will be working with a highly capable team of machine learning engineers and will have the opportunity to make a meaningful impact on the growth of a burgeoning industry.
As a Machine Learning Research Engineer, your responsibilities will include:
- Researching and implementing new machine learning techniques for use in Qeexo products
- Creating machine learning solutions for new applications from start to finish: from formulation of the problem to a commercial-grade solution
- Designing, writing, and maintaining software supporting Qeexo’s machine learning pipeline and research codebase
- Designing and executing experiments to advance our understanding of machine learning with time-series sensor data and related techniques
Ideal Candidate
- A proven track record of academic and/or industry experience in fields related to machine learning using time-series data
- Deep knowledge of statistical and machine learning approaches and problem domains
- Computer Science/EE/ECE background (MS or PhD preferred) with strong coding ability and proficiency with Python or other OOP language
- Proven success with multiple ML/AI/classification projects (research papers, Kaggle, open-source implementations, etc.)
- Expertise in one or more specific areas of research: automated machine learning, anomaly detection, condition monitoring, predictive maintenance, neural nets, deep learning, signal processing, digital imaging, ensemble learning, and system identification
- Experience with embedded programming
- Experience with model quantization/compression techniques
- Research-minded, ability to run experiments independently and present results to leadership and external clients
- Comfortable working in a terminal environment, writing scripts (Bash/Python) to process data and implement algorithms
- Experience in mobile or sensor platforms with microcontroller units
Skills & Requirements:
- Machine Learning (expert; at least 2-3 years industry experience and/or Master’s degree in relevant field)
- Python or other modern OOP language (proficient)
- Data Structures and Algorithms (proficient)
- Deep Learning (proficient)
- Ensemble Modeling/Classification (proficient)
- Data Structures and Algorithms (familiar)
- Signal Processing (familiar)
- Some travel may be required
- US Work Authorization required
Bonus Qualifications
- Experience building machine learning pipelines
- Experience with Docker and AWS
- Experience with large-scale data processing tools like Apache Spark
- Experience with PostgreSQL
- Significant work experience deploying production machine learning models with industrial customers