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Job Summary:

Western Governors University is hiring a Principal Machine Learning Engineer to join our team onsite in Salt Lake City, Utah.

The Principal Machine Learning Engineer at WGU is both a visionary leader and a hands-on builder. You serve as a technical leader on the most demanding, cross-functional projects and lead the team to build AI/ML products, particularly NLP and LLM, and execute large NLP/LLM models on a cloud environment at scale. As a principal member of the team, you work on our hardest problems and make the toughest decisions. You have strong technical judgment and influential skills to advocate good ML practices, challenge the current state, propose innovative ideas, and drive business-critical discussions. You can provide architectural guidance and detailed technical direction while fostering a continuous delivery culture. The perfect candidate should be able to educate stakeholders and mentor team members and, with a strong vision for how the ML discipline can proactively create positive impacts, have a significant stake in defining the future of the Ed Tech function for WGU. 

Essential Functions and Responsibilities:

• Work closely with the managers to define NLP initiatives, roadmaps, and strategies. 
• Collaborate with business stakeholders and product team to understand and convert business requirements into requisite NLP capabilities. 
• Lead the architecture, design, and development of complex AI systems. 
• Possess expert knowledge in our ML solutions and systems and ensure scalability, performance, and maintainability. 
• Drive best ML development and validation practices, code reviews, and documentation. 
• Execute the entire ML development lifecycle, including model research, data processing, model training and fine-tuning, model experimenting and evaluation, model improvement, and model deployment. 
• Research, Develop, deploy, and optimize state-of-the-art GenAI/NLP/LLM/Agent models for diverse NLP applications. 
• Collaborate with the Data Engineer team to develop and implement the data processing pipeline to ensure high-quality input for model training and inference. 
• Collaborate with the MLOps team to deploy ML/LLM models to the production environment, ensuring scalability, reliability, and performance. 
• Collaborate with the Software, Infrastructure, and Security teams to integrate ML solutions seamlessly into the WGU ecosystem. 
• Stay current with AI Agent, LLM, NLP, and Deep Learning technologies, and proactively apply them to our use cases to drive WGU innovation. 
• Provide technical leadership and mentorship to a team of ML engineers. Assist in their career development and help managers guide the career growth of their team members. 

Knowledge, Skill and Abilities:

• Strong background in machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, transformer, reinforcement learning, etc. 
• Experience operating high-availability, fault-tolerant, scalable, distributed software/infrastructure in production utilizing GitOps practices (Terraform preferred). 
• Experience with DevOps/MLOps frameworks (Databricks, GitHub Actions, MLFlow, Seldon, Sagemaker, DVC, etc.). 
• Experience with one or more deep learning frameworks like PyTorch, TensorFlow, Hugging Face, etc.
• Strong background in Python programming. 
• Substantial experience operating big data infrastructure in a cloud-based ecosystem (AWS, Databricks, Azure, GCP, etc.). 
• Experience with stream-processing systems (ksqlDB, Spark Streaming, Kafka, Apache Beam/Flink, etc.). 
• Experience with software engineering standard methodologies (unit testing, load testing, code reviews, design documents, continuous delivery). 
• Experience building data ETL pipelines.
• Develop and deploy production-grade services, SDKs, and data infrastructure emphasizing performance, scalability, and self-service. 
• Ability to conceptualize and articulate ideas clearly and concisely. 
• Entrepreneurial or intrapreneurial experience leading the creation of a new product & organization. 

Job Qualifications:

• M.S. degree or higher in Computer Science, Software Engineering, Data Science, Machine Learning/Deep Learning, Math, Physics, or any related field. 
• Prior experience in a senior or lead engineering role. ML domain is preferred. 
• 10+ years of industry experience in Software Development within a cloud environment. 
• 8+ years of industry experience building large-scale Machine Learning or Deep Learning models, carrying out the entire ML development lifecycle from POC to production release.

To explore more about our company and what makes working here special, visit our website at https://www.wgu.edu/about.html. To view current career opportunities and apply, please visit https://www.wgu.edu/about/careers.html.
 

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#D&I 

The salary range for this position takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.

At WGU, it is not typical for an individual to be hired at or near the top of the range for their position, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is:
 

Pay Range: $197,000.00 - $305,300.00

How to apply: apply online

Full-time Regular Positions (FT classification, standard working hours = 40)

This is a full-time, regular position that is eligible for bonuses; medical, dental, vision, telehealth and mental healthcare; health savings account and flexible spending account; basic and voluntary life insurance; disability coverage; accident, critical illness and hospital indemnity supplemental coverages; legal and identity theft coverage; retirement savings plan; wellbeing program; discounted WGU tuition; and flexible paid time off for rest and relaxation with no need for accrual, flexible paid sick time with no need for accrual, 11 paid holidays, and other paid leaves, including up to 12 weeks of parental leave.

The University is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.