Senior Machine Learning Engineer

Workday, Inc. (old); Dublin; On-site; EUR 120,000 - 160,000; Full time

Job summary

Workday, Inc. in Dublin, Ireland is seeking a Senior Machine Learning Engineer to join the Adoption Team.

You will design and productionize ML models within Workday's distributed systems, collaborating with engineering leads and product managers to deploy production-grade ML solutions and integrate generative AI capabilities. You will own end-to-end ML lifecycles, apply MLOps practices, mentor engineers, and help shape the technical roadmap for ML across the platform.

Qualifications

• Substantial professional experience in ML engineering with production deployments.
• Strong software engineering for distributed, production-grade systems.
• Proficiency with Python and ML frameworks (PyTorch/TensorFlow) and with MLOps practices.
• Ability to work with a good degree of independence - contributing to technical direction and delivery.
• Demonstrated technical leadership and collaboration skills including mentoring.
• Experience designing and developing Generative AI and LLM integration in production.

Responsibilities

• Design, build, and productionize ML models and pipelines in Workday's platform.
• Refine MLOps practices including deployment and monitoring.
• Ensure ML solutions scale across multi-tenant architecture.
• Own end-to-end ML lifecycle from data strategy to deployment and monitoring.
• Collaborate with product management, data engineering, and platform teams.
• Provide technical guidance and code/design reviews to engineers.
• Evaluate new ML tools and frameworks to stay current.
• Contribute to the ML roadmap for the Adoption team.
• Design and deploy Generative AI capabilities and LLM applications

Skills

Machine learning engineering

Distributed systems

Python

PyTorch/TensorFlow

MLOps

Generative AI

LLM integration

Technical leadership

Education

MS/PhD in Computer Science or ML

Tools

LangChain

Job description

Your work days are brighter here.

We're obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you'll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We're in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you'll do meaningful work with Workmates who've got your back. In return, we'll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you've found a match in Workday, and we hope to be a match for you too.

About the Team

The Adoption Team develops intelligent agents and capabilities that enable customers to manage Workday efficiently and maximize their overall experience. As a distributed-systems focused engineering group, we build and scale the agentic administrative tooling which supports Workday's core product suite.

About the Role

In this senior individual-contributor role as a Senior Machine Learning Engineer, you will bring strong applied ML expertise to a high-performing team of distributed-systems engineers, contributing to technical strategy and automation across Workday's administration platform. Working closely with Engineering leads and Product Managers, you will help shape technical approach, build and deploy production-grade ML systems, and support fellow engineers while partnering with core platform teams to integrate machine learning into Workday's administrative systems.

Drawing on your solid industry background, you will work effectively within a collaborative ecosystem, turning technical capabilities into measurable business impact for Workday customers.

Key Responsibilities

• Design, build, and productionize machine learning models and pipelines that integrate with Workday's platform-level systems.
• Apply and help refine best practices for ML engineering within the team, including model development, evaluation, deployment, and monitoring.
• Partner with distributed-systems engineers to ensure ML solutions scale reliably across Workday's multi-tenant architecture.
• Own significant pieces of end-to-end ML lifecycle work - from problem framing and data strategy through model training, deployment, and performance monitoring in production.
• Collaborate cross-functionally with product management, data engineering, and platform teams to identify opportunities for ML-driven automation and intelligence.
• Provide technical guidance and code/design review to other engineers on ML system design and implementation.
• Evaluate new tools, frameworks, and techniques to help keep the team's ML practices current and effective.
• Contribute to the technical roadmap for ML capabilities within the Adoption team.
• Design and deploy Generative AI capabilities and Large Language Model (LLM) applications

About You

Basic Qualifications

• Substantial professional experience in machine learning engineering, applied ML, or a closely related discipline, with a track record of shipping ML systems to production.
• Strong software engineering fundamentals, including experience building and operating distributed, production-grade systems.
• Proficiency with common ML frameworks and languages (e.g., Python, PyTorch/TensorFlow) and with MLOps practices (model versioning, CI/CD for ML, monitoring).
• Ability to work with a good degree of independence - contributing to technical direction, participating in architecture discussions, and driving projects from concept to delivery.
• Demonstrated technical leadership and collaboration skills through experience with cross-team initiatives, establishing technical standards, and mentoring junior and mid-level engineers.
• Demonstrated experience designing and developing with Generative AI technologies and LLM integration in production systems.

Other Qualifications

• 7+ years of experience working within large-scale, multi-tenant SaaS platforms.
• Background in applying ML to enterprise/administrative platform problems (e.g., anomaly detection, automation, intelligent configuration).
• Hands-on familiarity with LLM orchestration frameworks (preferably LangChain) and AI agentic architectures.
• Experience with cloud infrastructure and large-scale data processing systems.
• Advanced degree (MS/PhD) in Computer Science, Machine Learning, or a related field, or equivalent practical experience.

Workday Pay Transparency Statement (For EU Locations Only)

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