Senior Machine Learning Engineer

If you’re passionate about building a better future for individuals, communities, and our country—and you’re committed to working hard to play your part in building that future—consider WGU as the next step in your career.

Driven by a mission to expand access to higher education through online, competency-based degree programs, WGU is also committed to being a great place to work for a diverse workforce of student-focused professionals. The university has pioneered a new way to learn in the 21st century, one that has received praise from academic, industry, government, and media leaders. Whatever your role, working for WGU gives you a part to play in helping students graduate, creating a better tomorrow for themselves and their families.

Essential Functions and Responsibilities:

The Senior Machine Learning Engineer builds Machine Learning models, particularly NLP and LLM, and executes large NLP/LLM models on a cloud environment at scale. This role is essential in experienced learning, advancing machine learning skillset and sharing knowledge with others. As a senior member of the team, the Sr. ML Engineer works well individually and in a team. You have a passion for Machine Learning and enjoy researching start-of-the-art NLP and LLM techniques and applying them to the education domain. You have initiative and follow through with your tasks, while communicating with peers on status. The Senior Machine Learning Engineer applies direct ML knowledge and skills to make a direct impact on improving student learning experiences at WGU. This role has the courage to challenge the current state and propose innovative ideas. As a great communicator, the Senior Manager Learning Engineer works with cross-functional teams.  

Essential Functions and Responsibilities:  

• Works closely with the MLE manager to define NLP initiatives, roadmaps and strategies. 

• Collaborate with the product team and project stakeholders to convert business requirements into requisite NLP capabilities. 

• Develops, deploys, and optimizes state-of-the-art LLM models for diverse NLP applications. 

• Utilizes NLP/LLM techniques to discover valuable insights from unstructured data sources such as call transcripts, emails, mentor notes, etc. 

• Utilizes generative AI to build the next generation learning experience for our WGU students. 

• Executes the entire ML development lifecycle including model research, data processing, model training and fine-tuning, model experimenting and evaluation, model improvement, as well as model deployment. 

• Collaborates with the Data Engineer team to develop and implement the data processing pipeline to ensure high-quality input for model training and inference. 

• Collaborates with the MLOps team to deploy ML models to production environment, ensuring scalability, reliability, and performance. 

• Collaborates with the Software, Infrastructure, and Security teams to integrate ML soluctions seamlessly into WGU eco-system. 

• Stays up to date with the state-of-the-art technologies of LLM, NLP, and Deep Learning, and proactively apply them to our use cases to drive innovation of WGU. 

• Works with other team members to create standards and guidelines for ML. 

• Follows Agile, ML best practices and company’s processes. 

• Communicates status and updates with leadership, team members and other teams. 

• Mentors and provides guidance to junior team members. 

• Investigates trends and needs for ML models. 

• Performs other related duties as assigned. 

Knowledge, Skill and Abilities: