Research Intern, AI Machine Learning

Company

Seagate Technology

Designation

Research Intern, AI Machine Learning

Date Listed

12 Aug 2025

Job Type

Entry Level / Junior Executive

Intern/TS

Job Period

From Jan 2026, For At Least 6 Months

Profession

Sciences / Laboratory / R&D

Industry

Artificial Intelligence / Smart Automation

Location Name

26 Ayer Rajah Crescent, Singapore 139944, Singapore

Address

26 Ayer Rajah Crescent, Singapore 139944

Map

Allowance / Remuneration

$1,300 monthly

Company Profile

At Seagate, we know that data is always in motion, alive, connected—and we harness it in order to maximize human potential. Since 1979, we have been creating precision-engineered data storage technologies that deliver superior capacity, speed, safety, and performance. We are a diverse workforce of 30,000+ creative, hard-working, passionate people all over the world—Silicon Valley, the United Kingdom, Singapore, India, China, and beyond.

Job Description

About our group:

Seagate Research Group (SRG) conducts research to transform Seagate's considerable technical expertise, innovation, and manufacturing excellence to develop innovative technologies for the rapidly growing datasphere.

SRG's Software and Applied AI Research section conduct research in applying Machine Learning for Seagate advance project, products, and processes.

We use State-of-the-Art ML methods to develop applications and Proof-of-Concepts. Our projects include applying ML in the following areas - Video Surveillance, Predictive Maintenance for HDD, optimizing data storage solution, Sensor-fusion for Augmented Reality and more.

About the role - you will:

As a Research intern, you will have the opportunity to apply ML techniques to a variety of impactful projects within SRG's Software and Applied AI Research team. These include:

• Applying predictive analytics for Hard Disk Drive (HDD) applications.
• Optimizing data flow throughput for Storage solutions with ML.
• Developing AI solutions tailored at the edge
• Profiling and analyzing AI workloads
• Engaging in simulation and modeling using Physics-Informed Machine Learning models (Theory-Trained Models)
• AI Driven Material Discovery

About you:

We are looking for someone who is:

• A self-motivated and independent learner with a strong mathematical foundation in linear algebra, statistics, optimization, and calculus.
• Proficient in understanding Machine Learning and Deep Learning frameworks such as TensorFlow and PyTorch.
• Familiar with various ML approaches, including Supervised, Unsupervised, and Reinforcement Learning.
• Keen to stay updated on the latest ML developments and trends, such as Generative AI, Transformers, GPT, GANs, Autoencoders, and Diffusion AI, Physics-informed Neural Network.
• Possessing a proactive, can-do attitude, with a perpetual curiosity and willingness to learn
• Able a full time semester internship (Jan to May/Jul) .

Your experience includes:

• Currently pursuing a Bachelor's or Master degree or PHD in Computer Science, Engineering, Mathematics or a related field.
• Proficient in Python, with experience in TensorFlow, PyTorch, R-programming, and a lower-level programming language (C/C++ or Java).

• Knowledge or experience in one or more of the following areas:

• Applied reinforcement learning algorithms like Q-Learning or genetic algorithms in real-world applications.

• Machine Learning for vision or natural language processing (NLP)

Location:

The Shugart site (named after Seagate's founder, Al Shugart) is a research and design center. Easily accessible from the One-North MRT Station, many employees choose to take mass transportation to work. Being a purpose-built building, The Shugart has excellent employee recreational facilities. Take an active break at our badminton courts, table tennis tables, in-house gym, and recreation rooms. Our yoga and Zumba classes are very popular. We also offer classes and interest groups in photography, gardening, and foreign languages, and have various on-site celebrations, and community volunteer opportunities

Application Instructions

Please apply for this position through our Career Portal via the link below.

Kindly note that only shortlisted candidates will be notified.

Apply for this position