LLM Researcher

Description

• Deploy machine learning models into production using cutting-edge deployment strategies and conduct A/B tests to objectively measure performance improvements
• Innovate and optimize the machine learning workflow, from data exploration and model experimentation to production deployments on cloud platforms such as GCP or Azure
• Publish NLP or Machine Learning research papers in top AI journals or conferences
• Continuously innovate and optimize the machine learning workflow, from data exploration and model experimentation to production deployment
• Collaborate with Generative AI Centre of Excellence leaders and Equinix business units to assist in deciding between purchasing off-the-shelf generative AI tools and building solutions from foundational models for various generative AI applications
• Research and implement advanced Large Language Models (LLMs)
• Apply cutting-edge technologies and toolchains in big data and machine learning to build a robust machine learning platform on the cloud (MLOps)
• Develop features, conduct tests, perform statistical analyses, and interpret results to drive insights
• Utilize complex agents with platforms like Google Agentspace, Microsoft CoPilot, and Salesforce Agentforce
• Develop model pipelines in a development environment, manage version control with Git, utilize GitHub Actions, containerize applications, and deploy them to virtual machines, App Engine, or Kubernetes clusters

Requirements

• Excellent time management, communication, and organizational skills
• Architect LLM solutions that integrate agents built on different clouds or applications into a unified platform
• (Good to have) Envision, implement, and deliver production-level classical machine learning models (regression, classification, clustering), NLP models (sentiment analysis, summarization, chatbot/Q&A, information retrieval), and computer vision applications (image classification, object detection, semantic segmentation, and instance segmentation using YOLO V7, DDRNet, RFTM with pre-trained datasets like COCO and Cityscapes)
• Articulate research findings into patents
• Proficiently use deep learning frameworks such as PyTorch and TensorFlow
• Strong understanding of software engineering principles and design patterns
• Proficiency in Python programming is essential
• PhD with 4+ years of experience, Master’s with 3+ years, or Bachelor’s with 6+ years in Data Science, Computer Science, or Machine Learning
• Experience with at least one major cloud platform
• Ability to effectively communicate analysis results and insights
• Possess in-depth knowledge of NLP fundamentals, including transformers, attention models, and text pre-processing

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance