Software Engineer, Large User Models, Core Machine Learning

$136,000 - $200,000/Yr

Google - Mountain View, CA

Full-time - Entry Level

Mountain View, CA

10,001+ employees

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About the position

As a Software Engineer in the Large User Models team within Google Cloud's Core Machine Learning organization, you will develop and enhance machine learning models that impact billions of users. This role involves working on critical projects that leverage advanced machine learning techniques, particularly in the areas of Large Language Models, NLP, and Generative AI. You will collaborate with cross-functional teams to innovate and improve product offerings through applied research and development of scalable solutions.

Responsibilities

• Conduct applied research to improve the quality and training/serving efficiency of Large Transformer-based User Models.
• Build, improve, and productionize Large Transformer-based User Models.
• Experiment, analyze, and iterate over Large User Models for Google products (e.g., Play, Search) to improve model quality.
• Collaborate with researchers to develop new Machine Learning (ML) architectures, techniques, and metrics.
• Research in recommendation systems and Large Models from other domains (e.g., Language, Vision, Multimodal).

Requirements

• Bachelor's degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence or deep learning.
• Experience with Large Language Models, NLP or Generative AI.

Nice-to-haves

• Master's degree or PhD in Computer Science or related technical field.
• Experience training and improving deep learning models (e.g., multi-task models, sequence modeling, Long Short-Term Memories (LSTMs), Convolutional Neural Networks (CNNs), Attention).
• Experience with transformer models or recommendation systems.
• Experience with the modern ML stack or TPUs.
• Experience with applied ML and infrastructure.
• Excellent publication record in conferences (e.g., NeurIPS, RecSys).

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• 401(k) plan
• Paid holidays
• Paid time off
• Flexible scheduling
• Professional development opportunities
• Employee stock purchase plan
• Tuition reimbursement
• Wellness programs