Generative AI & Machine Learning Engineer Intern

Seagate Technology

68d • $30 - $43

About The Position

Our organization specializes in Global Data Analytics and provides comprehensive solutions for Big data, Generative-AI, and MLOps frameworks and deployments. We are a proactive, solution-focused, and collaborative team that partners with various business groups across the organization to deliver end-to-end solutions. In this highly visible role, you will help develop and optimize Large Language Model based analytics solutions to revolutionize business operations. Be part of a product team of about 20 Data science, ML and Platform Engineers that are the crux for developing and maintaining Machine Learning /advanced analytics platforms and Big Data Solutions. Leverage commercial (e.g. Azure Openai) or open source (e.g. Llama) LLMs to help end users intuitively and efficiently accelerate their daily workflows. Work on seamless integration of LLM models with existing platforms. Collaborate with machine learning engineers to build scalable data pipelines and development of new ML models. Design and implement tools and processes for the entire ML Ops including model development, model deployment, model serving, model monitoring and experimentation. Collaborate with data scientists, data engineers and Business SMEs to end-to-end Analytics platform and supporting infrastructure.

Requirements

• Proven hands-on or research experience in developing Natural Language Processing models.
• Experience in training and deployment of deep learning solutions in TensorFlow or PyTorch.
• Understanding and experience with generative AI tools, techniques and frameworks.
• Robust programming background in Python.
• Excellent understanding of machine learning algorithms & principles.
• Familiarity with cloud platforms such as AWS, Google Cloud, or Azure.
• Familiarity with SQL.
• Currently pursuing Masters or PhD degree in Computer Science, Machine Learning Engineering, Statistics, or related fields.

Responsibilities

• Develop and optimize Large Language Model based analytics solutions.
• Be part of a product team of Data science, ML and Platform Engineers.
• Leverage commercial or open source LLMs to accelerate user workflows.
• Integrate LLM models with existing platforms.
• Collaborate with machine learning engineers to build scalable data pipelines.
• Design and implement tools and processes for ML Ops.
• Collaborate with data scientists, data engineers and Business SMEs.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Participation in the employee stock purchase plan
• 12 paid holidays
• Minimum of 48 hours of paid sick leave

What This Job Offers

• Job Type: Part-time
• Career Level: Intern
• Education Level: Master's degree
• Number of Employees: 5,001-10,000 employees