About our group:

The Data Analytics (DA) team in the Characterization and Analytics Group develops big-data analytics, machine learning (ML), artificial intelligence (AI), and production software technologies that support R&D design and development activities within the Recording Head Technology organization.

Our work connects engineering data, Linux compute clusters, production data pipelines, monitoring, and AI-enabled analysis to help R&D teams move from data to decisions more efficiently.

Help modernize the data and compute systems behind next-generation recording-head R&D. You will build practical monitoring and automation solutions, improve production data flow, and explore frontier AI approaches such as natural-language-to-SQL and causal root-cause analysis.

About the role - you will:

· Modernize and improve the efficiency of Linux cluster management and data-analytics production workflows.

· Develop monitoring capabilities that show production data volume and flow, including how much data enters and leaves pipelines, processing status, throughput, failures, delays, and resource utilization.

· Analyze production workflows to identify bottlenecks, repetitive manual steps, reliability risks, and automation opportunities.

· Design and implement dashboards, alerts, logs, and operational metrics that improve visibility into production health and data quality.

· Prototype frontier AI solutions, including large language model (LLM) applications that translate natural-language questions into safe, validated SQL queries.

· Explore root-cause analysis (RCA) methods using causal analysis, statistical techniques, machine learning, and engineering domain knowledge.

· Develop maintainable software and automation in Python and Rust, with appropriate testing, documentation, and version control.

· Work with R&D engineers, data analysts, and infrastructure partners to define requirements, evaluate solutions, and communicate findings.

· Document designs, code, results, and recommendations, and present progress and insights to teammates and stakeholders.

About you:

· You are curious about how data, software, infrastructure, and AI work together in real production environments.

· You approach ambiguous technical problems with structured thinking, experimentation, and attention to data quality.

· You can work independently while collaborating effectively in a cross-functional, high-technology R&D environment.

· You communicate clearly, seek feedback, and turn prototypes into documented, reusable solutions.

· You are motivated to learn new technologies and evaluate them based on measurable engineering value.

Required Skills

· Python

· SQL

· Linux

· Data pipeline and production monitoring

· Software engineering and Git

Your experience includes:

· Programming experience with Python, including data processing, automation, APIs, testing, or analytics applications.

· Working knowledge of SQL and relational data concepts, including querying, joins, validation, and performance-aware data access.

· Experience using Linux and command-line tools for software development, data processing, or compute workloads.

· Understanding of software engineering practices such as Git version control, modular design, debugging, testing, and documentation.

· Familiarity with data pipelines, production monitoring, observability, or workflow automation.

· Foundational knowledge of machine learning, statistical analysis, or AI application development.

· Strong analytical, troubleshooting, and problem-solving skills.

You might also have:

· Experience with Rust or another systems programming language, or a strong interest in learning Rust for reliable, high-performance services and tools.

· Experience with high-performance computing or cluster technologies such as Slurm, containers, job scheduling, resource monitoring, or distributed workloads.

· Experience building dashboards or monitoring systems using tools such as Grafana, Prometheus, Power BI, Streamlit, or similar technologies.

· Knowledge of LLM application patterns such as tool use, retrieval-augmented generation, structured outputs, guardrails, evaluation, or natural-language-to-SQL workflows.

· Experience with causal inference, Bayesian methods, time-series analysis, anomaly detection, fault trees, or other RCA methods.

· Familiarity with REST APIs, Docker, Kubernetes, CI/CD, message queues, or workflow orchestration.

· Experience working with engineering, manufacturing, experimental, log, image, or time-series data.

 Master's or PhD student studying in Computer Science, Data Science, Software Engineering, Electrical Engineering, Mechanical Engineering, Physics, or a related engineering or quantitative field and must be continuing school into Fall 2027 semester. 

Location:

Our Normandale campus spans two suburbs, Edina and Bloomington, and serves as the Recording Head development and manufacturing arm of Seagate. Located in the heart of a bustling community, Seagate offers an on-site café, or if you prefer, you can drive to one of many restaurants just minutes away. Need to grab a gift over lunchtime? Shopping is abundant in the area. If working out is your thing, the on-site fully equipped fitness center hosts wellness programs, outdoor activities, tournaments, and group workouts. Looking for something more laid back? Reset in one of our meditation rooms, or simply take a walk around our indoor walking path. On-site cultural festivals, celebrations, and community volunteer opportunities also abound.

The estimated base wage range for this position is $35.00-45.00/hr. The individual base wage is based on work location and additional factors, including job-related skills, experience, and relevant education or training. Seagate offers comprehensive benefits to its eligible Interns, including, but not limited to, medical, dental, vision, and participation in the employee stock purchase plan.  Seagate also offers Interns 12 paid holidays and a minimum of 48 hours of paid sick leave.  The benefits for this position are based on a 24 to 40-hour-per-week schedule for a full calendar year and may differ depending on work location and tenure with the Company. 
 
#internship 

Location: Normandale, United States
Travel: None