Machine Learning Engineer

Job Description

Senior Machine Learning Engineer – AI Platform | Workday

The Tone:
This is a full-time role at Workday, located in Boulder, CO with a hybrid work model. Workday operates as a Fortune 500 company and a leading AI platform for managing people, money, and agents, aiming to shape the future of work by building AI-powered software that impacts millions daily. The company’s culture is rooted in integrity, empathy, and shared enthusiasm, encouraging collaboration and bold ideas to tackle big challenges. Joining Workday means doing meaningful work with colleagues who support each other, in a company invested in long-term growth and development.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: Hybrid – Boulder
• Pay: $171600–$257400 USD yearly
• Team: AI Core team, part of Workday’s AI Platform organization
• Mission: Develop tailored user experiences using advanced Agentic AI, LLMs and RAG to deliver critical AI platform capabilities and deep-value agent applications.
• Tech Stack: Python, Docker, Kubernetes, PySpark, PyTorch, TensorFlow, Sklearn, Pandas, AWS, GCP

What You’ll Actually Do
• Design: Own exploration, design, and implementation of features for sophisticated ML platforms, pipelines, and services.
• Evaluate: Be responsible for the evaluation, scalability, and observability of these machine learning features.
• Apply: Apply machine learning techniques, including LLMs and natural language understanding, to analyze large HR and Finance text datasets.
• Innovate: Stay up to date with advancements in AI, LLMs, RAG, autonomous agents, and orchestration frameworks to drive innovation.
• Mentor: Serve as a technical role model and guide for more junior engineers on the team.

The Must-Haves
• Background: Bachelor’s degree in engineering, data/computer science, physics, math or equivalent. This is a Senior-level role.
• Experience: 6+ years as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including through applied research, design, implementation, production, and production-based evaluation. 5+ years of professional experience with Python and supporting numeric libraries, with experience shipping production code and models. 5+ years of professional experience with cloud computing platforms (e.g. AWS, GCP, etc.).
• Skills: Deep Python expertise and solid software engineering skills for writing well-designed production code; developing and deploying new APIs/services using Docker/Kubernetes at scale; strong experience with machine learning and deep learning frameworks & toolkits such as PySpark, PyTorch, TensorFlow, and Sklearn; professional experience with data engineering and data wrangling using tools like Pandas and PySpark; deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases; professional experience in independently solving ambiguous, open-ended problems and technically leading teams; ability to communicate clearly and effectively in a cross-functional setting.
• Bonus: Master’s or PhD preferred. 3+ years of experience in building information retrieval systems and/or graph-based recommendation systems. 3+ years of hands-on professional experience in developing large language models (LLMs), text generation models, or graph-based machine learning models for production, including data processing, model fine-tuning, model deployment, and model evaluation. 3+ years of experience building services to host machine learning models in production at scale.