Intern - Firmware & Product Testing AI/Machine Learning
Skip the busywork
ApplyBolt rewrites your resume for this exact role and hits submit. You just pick the jobs.
About this role
The Firmware & Product Test (FPT) team
The Firmware & Product Test (FPT) team at Micron Technology plays a critical role in validating firmware specifications for SSDs. The team develops detailed verification plans, implements them in Python, and ensures alignment with NVMe standards and security requirements. Testing spans white‑box, grey‑box, and black‑box methodologies across simulation, FPGA prototypes, and hardware environments.
The AI/Machine Learning Intern supports the FPT organization by applying Python programming and machine learning skills to enhance firmware test automation, data analysis, and anomaly detection. This role contributes directly to improving test efficiency, firmware quality, and product reliability while collaborating with experienced firmware engineers and data scientists.
Responsibilities
- Develop and refine Python‑based automation tools that enhance firmware test coverage and integrate machine learning techniques.
- Clean, preprocess, and analyze large firmware test datasets to identify insights, anomalies, and performance patterns.
- Assist in building, training, and tuning machine learning models that help predict firmware issues or detect abnormal system behavior.
- Evaluate model performance, troubleshoot issues, and document analysis results and recommendations.
- Collaborate with firmware engineers and data scientists to incorporate AI‑driven solutions into existing test workflows.
Minimum Qualifications
- Pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical/Computer Engineering, or a related technical field.
- Strong programming proficiency in Python and familiarity with libraries such as NumPy, pandas, and scikit‑learn.
- Solid understanding of machine learning fundamentals, model training concepts, and evaluation methods.
- Strong analytical and and problem‑solving skills with a foundation in mathematics and statistics.
- Ability to work effectively in a collaborative engineering environment and communicate technical concepts clearly.
Preferred Qualifications
- Experience with machine learning frameworks such as TensorFlow or PyTorch.
- Prior project or research experience in machine learning, data science, or AI (e.g., academic projects, Kaggle competitions).
- Familiarity with embedded systems, firmware, or hardware testing processes.
- Exposure to software development practices such as version control (Git) or agile methodologies.