Intern – Machine Learning (Gen AI)

Seagate

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Pune, India1 month ago

RoleIntern – Machine Learning (Gen AI)

LocationPune, India

QualificationPursuing Masters in CS / ML / Statistics

Job Description

As a Machine Learning Intern at Seagate, you will be part of a core product team of 12-15 engineers and data scientists. Your primary focus will be developing and optimizing Large Language Model (LLM) based solutions. You will leverage both commercial models, like Azure OpenAI , and open-source models, like Llama , to accelerate daily workflows for end-users. This role requires a seamless integration of AI models into existing Big Data platforms and supporting infrastructure.
In addition to model development, you will design and implement tools for the entire MLOps lifecycle —including deployment, serving, monitoring, and experimentation. You will collaborate with Business SMEs and Data Engineers to ensure that deep learning solutions are scalable and efficient. Success in this role requires a detail-oriented professional who can question complex problems and propose innovative, out-of-the-box AI solutions for the HiTech and manufacturing space.

Develop and optimize analytics solutions based on Large Language Models (LLMs).
Integrate commercial and open-source LLMs (Azure OpenAI, Llama) into business workflows.
Design and manage MLOps processes: development, serving, and monitoring.
Collaborate with cross-functional teams to build end-to-end analytics platforms.
Implement deep learning solutions using TensorFlow or PyTorch frameworks.
Write efficient Python code and manage data using SQL queries.
Participate in technical experimentation and model performance tuning.
Maintain clear documentation for AI workflows and supporting infrastructure.

Education: Currently pursuing a Masters in Computer Science, Machine Learning, Statistics, or related fields.
NLP Experience: Proven hands-on or research experience in Natural Language Processing (NLP).
AI Knowledge: Strong understanding of Generative AI tools, techniques, and ML algorithms.
Programming: Strong background in Python and familiarity with SQL.
Deep Learning: Experience in training and deploying models in PyTorch or TensorFlow .
Organization: Uncompromisingly detail-oriented with solid time management skills.
Communication: Excellent verbal and written abilities to instill commitment within a team.

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