data
Posted 22 hours agoMachine Learning Engineer III
at Workday
Usa Pleasanton, United StatesHybrid
Responsibilities
- Drive Meta-ML & Optimization: Develop algorithms for automated node-level optimization within agent graphs, identifying the best LLM and prompt configurations for every workflow step.
- Build recommender systems for engineering teams to drive optimal evaluation for their agents.
- Scale Evaluation & Observability: Engineer cloud-based pipelines (Kubeflow) and A/B testing frameworks for rigorous offline/online evaluation, failure attribution, and safety monitoring.
- Lead the ML Lifecycle: Own the end-to-end MLOps process—from exploration and prompt engineering to scalable production deployment—ensuring high-quality, reliable performance.
- Define Strategic Roadmaps: Independently identify ML opportunities, propose high-impact solutions to leadership, and integrate industry best practices across the organization.
- Collaborate with Autonomy: Work cross-functionally with PMs and Engineers to deliver "AI-first" products, enjoying full ownership of your work within a supportive, growth-oriented culture. About You Basic
Requirements
- 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.
- About the Team This is a very exciting opening in the AI Platform team in our Information Retrieval and Agent Evaluation team.
- The Agent Evaluation Platform project is the "Ground Truth" engine for Workday’s AI transformation and we have an ambitious roadmap.
- As Workday infuses AI Agents into every facet of our enterprise suite, our team provides the critical infrastructure and algorithms needed to prove they work—and make them better.
- The AI Platform Information Retrieval products are at the heart of Workday’s intelligence layer.
- Our products utilize advanced semantic search to navigate Workday’s massive data model, as well as turning natural language questions into precise SQL and Python executions.
- Workday’s AI Platform organization is bringing “AI first” products to life at every step of the Workday product offering.
- We’re looking for highly creative, results-focused, and deeply skilled Machine Learning Engineers/scientists to work with us on a range of these challenges. Why Workday? 1.
- You'll be working at the absolute frontier of Agentic AI - "how do we validate, scale, and optimize an agent" and "how do we extract the correct data for agents". 2.
- About the Role We are seeking pragmatic ML Engineers to drive the applied research, deployment, and optimization of our Agentic AI, Search, and Semantic Parsing products.
- If you are ready to apply creative problem-solving to global-scale ML systems, we want to hear from you.
- In this role, you would: Architect Agentic AI: Design and deploy sophisticated reasoning, planning, and swarm agents that interact seamlessly with enterprise data and support continuous, life-long learning.
- Advance Information Retrieval: Build hybrid, agentic search systems and semantic parsing products (Text-to-SQL/Python) utilizing vector search, reasoning, and fine-tuning for structured output.
- experience researching, developing and deploying production-grade ML systems, including expertise in deep learning, NLP, Information Retrieval, and recommender systems using frameworks like PyTorch or TensorFlow.
- Generative AI & Agentic Systems: Proven track record of building and evaluating NLP and LLM-powered products, including expertise in RAG architectures, agentic frameworks (e.g., LangChain/LangGraph), and long-context LLM applications (e.g., Text-to-SQL).
- experience with a focus on modular library design, asynchronous patterns, and scalable system architecture (state management/error handling) for non-deterministic AI outputs. Other
- Qualifications Academic Foundation: Advanced degree (Master’s or Ph.D.) in a quantitative field or a strong portfolio of peer-reviewed research publications.
- Optimization & Advanced Techniques: Proficiency in techniques like DSPy, Reinforcement Learning, imitation learning, graph neural networks, multi-modal models, and large-scale data processing (PySpark, SQL).
- experience in A/B testing, Knowledge Graphs, and "Golden Dataset" curation for model benchmarking. Data Pipelines: Proficiency in large-scale data processing (PySpark, SQL). Production MLOps: Hands-on
- experience with the full ML lifecycle, including model fine-tuning (PEFT), evaluation frameworks (e.g., DeepEval/RAGAS), and cloud-native deployment (Docker/K8s, AWS/GCP).
- Collaborative Leadership: Demonstrated ability to lead cross-functional teams, mentor junior engineers, and solve ambiguous problems with high autonomy.
Experience
- Qualifications: Deep Technical ML Capability: 3+ years of
- Engineering Excellence: 2+ years of Python
Benefits
- 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.
- Workday Pay Transparency Statement 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.
- Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things.
- Primary Location: USA.CA.Pleasanton Primary Location Base Pay Range: $160,000 USD - $240,000 USD Additional US Location(s) Base Pay Range: $136,200 USD - $240,000 USD Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in-person time and remote.
Additional details
- 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.
- 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.
- We believe if you do what you love, you’ll love what you do.
- We are part of a global, high-growth technology company and our team has the opportunity to develop the next generation of Workday’s groundbreaking collaborative products supporting a customer base of more than 31 million strong.
- Over 65% of the Fortune 500 are Workday customers.
- We bridge the gap between human language, search, and enterprise data, including reasoning over knowledge.