Entry Level AI/ML Engineer specializing in Machine Learning and Large Language Models (LLMs)

Job Description

Entry Level AI/ML Engineer specializing in Machine Learning and Large Language Models (LLMs) | IBM

The Tone:
This is an early career position at IBM, located in San Jose, CA. The IBM Automation and AI group is seeking a specialist in machine learning and Large Language Models (LLMs) to join their AI/ML Center of Excellence team. This role is crucial for implementing cutting-edge AI/ML capabilities across IBM’s Automation product portfolio, by leading data collection for LLM training, integrating LLM technologies into products, and establishing best practices.

The TL;DR
• Role: Early Career
• Location: San Jose, CA (In-person)

• Team: AI/ML Center of Excellence team at the IBM Silicon Valley Lab
• Mission: Implement cutting-edge AI/ML capabilities and establish best practices for Large Language Models across IBM’s Automation product portfolio.
• Tech Stack: IBM AI Model & Data Catalog, IBM Data & Model Governance, FM-Eval, Unitxt, Python, PyTorch, TensorFlow, JAX, TensorRT, ONNX, TorchServe, IBM Cloud, AWS, Azure, GCP, vector databases, embedding technologies

What You’ll Actually Do
• Data Pipeline Management: Design and implement robust data collection pipelines for LLM training and evaluation datasets, ensuring data quality and compliance with privacy regulations.
• LLM Integration & Deployment: Architect and implement solutions to integrate Large Language Models with IBM’s existing and emerging products, optimizing deployment across various computing environments.
• AI/ML Best Practices: Establish technical standards, create reusable components, and develop design patterns for effective AI/ML feature implementation across product teams.
• Model Performance & Ethics: Develop monitoring systems to track LLM performance, drift, and potential biases, and research responsible AI techniques like explainability and fairness.
• Innovation & Collaboration: Collaborate with cross-functional product teams to identify and drive opportunities for AI-driven innovation across IBM’s Automation product portfolio.

The Must-Haves
• Background: Bachelor’s or master’s degree or higher in Computer Science, Machine Learning, AI, or a related technical field, specializing in NLP and large language models (transformer architectures).
• Experience: Less than one year of experience in machine learning engineering or data science roles, with experience in data processing pipelines and working with large datasets.
• Skills: Strong programming skills in Python, familiarity with ML frameworks (PyTorch, TensorFlow, or JAX), knowledge of MLOps practices and tools, strong communication skills, and a problem-solving mindset.
• Bonus: Experience with fine-tuning and prompt engineering for LLMs, deep understanding of transformer architectures and attention mechanisms, proficiency in vector databases and embedding technologies, knowledge of model serving frameworks, and familiarity with cloud platforms.