Teradyne is looking to solve the problem of enhancing manufacturing test processes, driving automation, and unlocking actionable insights from production data through data engineering and machine learning.
Requirements
- Strong foundation in data structures, databases (SQL/NoSQL), and programming (Python, R, Java, or Scala).
- Exposure to machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and basic ML concepts.
- Proficiency in Microsoft Office (Excel, PowerPoint, Word, PowerBI) for reporting and presentation.
Responsibilities
- Participate in exploratory research projects focused on data-driven process optimization and automation.
- Investigate and prototype new data engineering solutions for collecting, cleaning, and integrating diverse manufacturing datasets.
- Experiment with machine learning models to predict outcomes, detect anomalies, and optimize test processes.
- Collaborate with senior engineers and R&D teams to evaluate the feasibility and impact of new technologies.
- Document findings, methodologies, and results to support knowledge sharing and future development.
- Present research outcomes and recommendations to technical teams and stakeholders.
- Stay current with advancements in data engineering, machine learning, and manufacturing analytics.
Other
- Minimum: Second semester Sophomore year in Computer Science, Data Science, Electrical Engineering, or a related field.
- Available for a 6-month co-op.
- Ability to communicate technical concepts clearly and collaborate in multidisciplinary teams.
- Analytical mindset and creative problem-solving skills.
- Position will be Hybrid in Agoura Hills, Ca (no relocation or housing assistance provided)
