Senior Machine Learning Engineer - AI Platform

About the role

The role involves developing tailored user experiences using advanced Agentic AI, LLMs and RAG. Responsibilities include collaborating with other engineers to deliver ML solutions across Workday's product ecosystem, and using current software and data engineering stacks to enable training, deployment, and lifecycle management of various ML models.

Responsibilities

• Own exploration, design and implementation of features for sophisticated ML platforms, pipelines and services.
• Be responsible for evaluation, scalability and observability of these features.
• Apply machine learning techniques including LLMs and natural language understanding to analyze large sets of HR and Finance-related text data.
• Design and launch pioneering cloud-based machine learning architectures.
• Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation.
• Serve as a technical role model for more junior engineers.

Requirements

• Bachelor’s (Master’s or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent.
• 6+ years experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation.
• 5+ years of professional experience with Python and supporting numeric libraries, with experience in shipping production code and models.
• 5+ years of professional experience with cloud computing platforms (e.g. AWS, GCP, etc.).

Qualifications

• 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.
• 3+ years of experience in machine learning and deep learning frameworks & toolkits such as PySpark, Pytorch, TensorFlow, and Sklearn.
• 3+ years of professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker.
• 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.

Other Qualifications

• 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.
• 3+ years of experience in machine learning and deep learning frameworks & toolkits such as PySpark, Pytorch, TensorFlow, and Sklearn.
• 3+ years of professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker.
• 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.

Benefits

Workday offers a comprehensive benefits package, including:

• Annualized base salary range: $171,600 USD - $257,400 USD for the primary location and $163,000 USD - $288,000 USD for additional US locations.
• The ability to spend at least half (50%) of your time each quarter in the office or in the field with our customers, prospects, and partners (depending on role).
• Opportunity to come together in our offices for important moments that matter.

Pay

The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants.

Schedule

We combine the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role).

Skills

Strong technical leadership with deep Python expertise and solid software engineering skills, capable of writing beautiful, well-designed code while delivering solutions efficiently.

Qualifications

• Bachelor’s (Master’s or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent.
• 6+ years experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation.
• 5+ years of professional experience with Python and supporting numeric libraries, with experience in shipping production code and models.
• 5+ years of professional experience with cloud computing platforms (e.g. AWS, GCP, etc.).