Generative AI/Machine Learning Engineer

$98,400 - $116,000/Yr

Seagate Technology - Fremont, CA

Full-time - Mid Level

Fremont, CA

Computer and Electronic Product Manufacturing

About the position

The Generative AI/Machine Learning Engineer role focuses on developing, fine-tuning, and deploying large language models and traditional machine learning models to extract insights from extensive datasets. The position involves collaborating with cross-functional teams to integrate generative AI innovations into various business products, enhancing performance and engagement. The ideal candidate will be passionate about the evolving technology landscape of Generative AI and possess strong problem-solving skills.

Responsibilities

• Develop, fine-tune, and deploy large language models for various applications
• Manipulate and build models (traditional ML and generative AI) to extract insights from large data sets
• Design and implement prompt engineering strategies to optimize model performance
• Utilize Retrieval-Augmented Generation (RAG) and related techniques to enhance model output
• Integrate generative AI innovations into Sales, marketing, Supply chain and other business products to improve performance and engagement
• Collaborate with cross-functional teams to identify and address AI-related challenges
• Stay updated with the latest trends and advancements in Generative AI and machine learning
• Adapt generative AI models for diverse machine learning tasks and applications

Requirements

• Proven experience with Large Language Models (e.g. OpenAi, Lama, Gemini) and prompt engineering
• Proficiency in Python, SQL, and ML frameworks like PyTorch and TensorFlow
• Ability to quickly generate working code with a Generative AI coding copilot
• Expertise in fine-tuning and deploying AI models in production environments
• Strong knowledge of Retrieval-Augmented Generation (RAG) and related techniques
• Masters Degree in Computer Science or Business Analytics

Nice-to-haves

• Experience with cloud platforms (e.g. Azure, AWS, Google Cloud) for model deployment
• Experience with DevOps tools like Git and Docker

Benefits

• Eligibility for variable pay bonus
• Medical insurance
• Dental insurance
• Vision insurance
• Life insurance
• Short-and long-term disability
• 401(k)
• Employee stock purchase plan
• Health savings account
• Dependent care and healthcare spending accounts
• Paid time off including 12 holidays
• Flexible time off
• Minimum of 48 hours of paid sick leave
• 16 weeks of paid parental leave