Machine Learning Engineer - Evisort

## Responsibilities - Help develop tailored user experiences using advanced LLMs, Knowledge Graphs, personalization, and predictive analysis. - Collaborate with other engineers to deliver ML solutions across Workday’s product ecosystem. - Utilize software and data engineering stacks to enable training, deployment, and lifecycle management of various ML models. - Develop and deploy new products at scale. - Leverage Workday’s vast computing resources on rich datasets to deliver transformative value to customers. - Contribute to feature and service development. - Have an approach of continuous improvement, passion for quality, scale, and security. - Be curious and prepared to question or challenge choices and practices where they don't make sense or could be improved. - Have a product approach and strong intuition around how ML can drive a better customer experience. - Demonstrate a strong sense of ownership and teamwork. ## Requirements - Basic Qualifications: - 5+ 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. - 2+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow. - 2+ years of professional experience in building services to host machine learning models in production at scale. - 2+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases. - 2+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.). - Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent. - Sr. MLE Qualifications: - 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. - 3+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow. - 3+ years of professional experience in building services to host machine learning models in production at scale. - 3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases. - 3+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.). - Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent. ## Nice to Have - Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation. - 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. - Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders. - Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement. ## Benefits - Work with a Fortune 500 company and a leading AI platform for managing people, money, and agents. - Build AI first products and automate manual work, freeing up customers' time and accelerating their businesses. - Join the Evisort AI team, which functions as a startup within Workday. - Build at the pace of innovation of a startup, while backed by the enormous support and impacting Workday’s incredible customer base of 70M+ users. - Be part of a culture rooted in integrity, empathy, and shared enthusiasm. - Have 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. - Inspire a brighter work day for everyone, including yourself.