Machine Learning Engineering Intern

Machine Learning Engineer Intern TDK SensEI San Clemente, CA

This position is for our San Clemente, CA office - only apply if you are based there or willing to relocate

At TDK SensEI, we are transforming how industrial customers utilize and interact with sensor data. We specialize in developing advanced AI solutions capable of running directly on edge devices. By processing data locally, TDK SensEI enhances real-time decision-making, privacy, security, and cost efficiency. Our offerings include automated machine learning tools, AI-powered condition-based monitoring systems, and various sensor devices optimized for low latency and power consumption. 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.

We are looking for a machine learning intern who loves working with sensor data, loves developing novel algorithms, and has strong curiosity about developing new GenAI-based ML applications. You will be working with a highly capable team of machine learning engineers and software engineers and will have the opportunity to make a meaningful impact on important new product development.

As a Machine Learning Engineer Intern, your responsibilities will include:

1. Assist in Model Development: Collaborate with senior engineers to develop and train machine learning models tailored for edge devices.

2. Data Collection and Preprocessing: Gather and preprocess data from various sensors and sources to ensure high-quality inputs for AI models.

3. Prototype Development: Develop and test prototypes for new Gen AI-based use cases, ensuring they meet performance and reliability standards.

4. Performance Evaluation: Conduct experiments to evaluate the performance of AI models and edge solutions, identifying areas for improvement.

5. Collaboration: Work closely with cross-functional teams, including machine learning and software engineers, to integrate AI solutions into prototype systems.

Ideal Candidate

. Signal processing and machine learning (most likely in EE major)

. Computer vision (most likely in CS major)

. Language model (most likely in CS major)
Deep knowledge of statistical and machine learning approaches and problem domains
Machine Learning/Computer Science/Electrical Engineering background with strong coding ability and proficiency with Python or other OOP language
Proven success with multiple ML/AI/classification projects (research papers, 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 working with GenAI applications
Comfortable working in a terminal environment, writing scripts (Bash/Python) to process data and implement algorithms

Skills & Requirements:
Master's or PhD student
Python or other modern OOP language (proficient)
Data Structures and Algorithms (proficient)
Deep Learning (proficient)
Data Structures and Algorithms (familiar)
Experience with Docker and AWS (familiar)
US Work Authorization required