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:
Utilizes NLP/LLM techniques to discover valuable insights from unstructured data sources such as call transcripts, emails, mentor notes, etc.
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 MLOps team to deploy ML models to production environment, ensuring scalability, reliability, and performance.
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.
Knowledge, Skill and Abilities:
Experience operating high-availability, fault-tolerant, scalable, distributed software/infrastructure in production utilizing GitOps practices (Terraform preferred).
Experience with existing MLOps frameworks (Databricks, Seldon, Sagemaker, DVC, etc.).
Experience with software engineering standard methodologies (unit testing, code reviews, design document, continuous delivery).
Develop and deploy production-grade services, SDK’s, and data infrastructure emphasizing performance, scalability, and self-service.
Organizational or Student Impact:
Problem Solving & Decision Making:
This individual builds, leads, and integrates multiple project teams and broad assignments, driving decisions and results.
Communication & Influence:
Works to influence others to accept and understand technical direction, new concepts, practices, and approaches. Requires ability to communicate and influence senior executive leadership regarding matters of strategic importance to the organization.
M.S. degree or higher in Computer Science, Software Engineering, Data Science, Machine Learning/Deep Learning, Math, Physics or any related field.
Deep understanding of NLP and LLM concepts, including language modeling, text classification, sentiment analysis, token embeddings, etc.
Hands on experience with one or more deep learning frameworks like PyTorch, TensorFlow, Huggingface, etc.
Experience with leading cloud and data platforms such as AWS, Azure, Sagemaker, Databricks, etc.
Preferred Qualifications:
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: $157,000.00 - $243,400.00
WGU will accept applications for this position until 12:00 AM ET, 07/31/2024
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.