Principal Machine Learning Engineer.

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Job Profile Summary:

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, 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 of them.
• Drive best practices for ML development and validation, 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, as well as 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 production environment, ensuring scalability, reliability, and performance.
• Collaborate with the Software, Infrastructure, and Security teams to integrate ML solutions seamlessly into WGU eco-system.
• Stay up to date with the state-of-the-art technologies of AI Agent, LLM, NLP, and Deep Learning, and proactively apply them to our use cases to drive innovation of WGU.
• 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.
• Follow Agile, ML best practices and company's processes.
• Communicate status and updates with leadership, team members and other teams.

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.).
• Strong background with either Python, Go, or Java programming experience.
• Substantial experience operating big data infrastructure in a cloud-based ecosystem (Databricks preferred).
• 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).
• Develop and deploy production-grade services, SDK's, 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.

Competencies:

Organizational or Student Impact:

• Works proactively; anticipates and prevents highly complex problems crossing disciplines.
• Develops and establishes technical/business processes.
• Will provide highly innovative solutions for extremely specialized, complex technical issues.
• Fully understands and quantifies program risks with broad, significant impact.

Problem Solving & Decision Making:

• Develops and accomplishes goals and objectives independently.
• This individual builds, leads, and integrates multiple project teams and broad assignments, driving decisions and results.
• Provides strategy and guidance to develop technical talent.
• Sets and models high standards for effective interactions across groups.

Communication & Influence:

• This individual communicates with experts within and outside the organization related to significant advancements specific to technology.
• 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.
• Frequently conducts briefings to senior leaders both within and outside of the technical function.

Leadership:

• Responsible for providing guidance, coaching, and training to other employees across the University within an area of expertise.
• Typically, responsible for managing large, complex project initiatives or strategic importance solutions to the organization, involving large cross-functional teams.
• Individual may have direct reports, but generally fewer than three.

Job Qualifications:

Minimum 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 cloud environment.
• 8+ years of industry experience in building large-scale Machine Learning or Deep Learning models, carrying out the entire ML development lifecycle from POC to production release.
• Deep understanding of NLP and LLM concepts, including language modeling, text classification, sentiment analysis, token embeddings, etc.
• Proficient programming skills such as Python, R, SQL, C/C++, etc.
• Hands-on experience with one or more deep learning frameworks like PyTorch, TensorFlow, Hugging face, LangChain, LlamaIndex, etc.
• Experience with leading cloud and data platforms such as AWS, Databricks, Azure, Sagemaker, etc.
• Experience with databases, data warehouses, data lakes, data ETL, feature engineering, and visualization techniques.
• Experience with open-source ML tools and APIs such as MLFlow, Streamlit, FastAPI, etc.
• Excellent problem-solving abilities to analyze complex data and requirements towards practical solutions.
• Excellent creative thinking skills to come up with new solutions and approaches.
• Strong communication and collaboration capabilities, working seamlessly with business stakeholders and cross-functional teams.
• Comfortable working in a fast-paced, highly collaborative, dynamic work environment.

Preferred Qualifications:

• PhD preferred.
• Experience with Databricks preferred.
• AWS cloud platform experience preferred.

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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:

WGU will accept applications for this position until 12:00 AM ET, 11/25/2024

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.

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