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R&D Data Analytics, AI and Production Systems - Summer 2027 Internship (Masters or PhD)

Pay
$35–45/hourLocation-specific pay — pay source
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
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Before you apply

New graduates
For current studentsJob title: R&D Data Analytics, AI and Production Systems - Summer 2027 Internship (Masters or PhD) (Bloomington, MN, US)

What you’ll work on

Full posting
  • Modernize Linux cluster management and data-analytics production workflows

  • Build dashboards, alerts, and metrics for production pipeline health

  • Analyze production workflows for bottlenecks and automation opportunities

  • Prototype LLM applications that turn natural-language questions into validated SQL

  • Explore root-cause analysis methods using causal, statistical, and ML techniques

From the employer’s posting
Modernize and improve the efficiency of Linux cluster management and data-analytics production workflows.
Design and implement dashboards, alerts, logs, and operational metrics that improve visibility into production health and data quality.
Analyze production workflows to identify bottlenecks, repetitive manual steps, reliability risks, and automation opportunities.
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.

What you’ll bring

All qualifications

Core experience

  • 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.
Qualification wording
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.
Education & alternatives
· 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:

About Seagate Technology

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.

In the employer’s words · Read in context

Apply at Seagate Technology

Posting record

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Actively hiringFirst seen by us 5 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 29, 20265 days ago
Recorded sightings
7
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 5

Similar jobs usually come down between day 5 and day 54.

From 10,736 similar postings that came down. Coming down is not always a hire.

Seagate Technology is hiring

24 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Takes jobs down at a usual pace
  • 8% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Rust
  • SQL
  • Docker
  • Grafana
  • Kubernetes
  • Power BI
  • Streamlit
Where the posting names them
· 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.
Required Skills · Python · SQL
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.
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.
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:
· 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.
· Python · SQL · Linux
· 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.
· 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.
· 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.
· 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.

Your next step

Complete your application on seagatecareers.com. The employer’s form will show what is required.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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

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