Senior Machine Learning Engineer
Western Governors University
- United States
- United States
À propos
Grade: Technical 411Pay Range: $157,000.00 - $243,400.00
Job Description The Senior ML Engineer builds and deploys state-of-the-art NLP/LLM models at scale in a cloud environment, with a focus on improving student learning experiences. You lead by example, mentor junior engineers, and collaborate across cross-functional teams. You actively research the latest NLP/LLM techniques and translate them into practical, scalable solutions for the education domain. You communicate clearly with leadership and peers, influence product directions, and drive innovation that challenges the status quo.
Key Responsibilities Strategic leadership
Define NLP initiatives, roadmaps, and success metrics in collaboration with the MLE manager.
Champion best practices in ML, data governance, and security within the team and across the organization.
Mentor junior engineers and serve as a technicalleadon complex ML projects.
Model research, development, and deployment
Research and prototypestate-of-the-artNLP/LLMtechniques;evaluate and select approaches suitable for production.
Develop, train, fine-tune, andoptimizeproduction-grade NLP/LLM models.
Deploy models to production with emphasis on performance, scalability, reliability, and observability.
Data, pipelines, and collaboration
Partner with Data Engineering to build robust data processing pipelines and high-quality training/inference data.
Work withMLOpsto ensure scalable, reproducible deployment, monitoring, and model governance.
Collaborate with Software, Infrastructure, and Security teams to integrate ML solutions into the university ecosystem.
Product impact and stakeholder engagement
Translate business requirements into NLP capabilities; collaborate with product stakeholders tovalidateoutcomes.
Apply NLP insights to unstructured data sources (e.g., transcripts, emails, mentor notes) to inform learning experiences.
Continuous improvement and learning
Stay current with NLP/LLM, DL, and AI trends; proactively apply innovations to use cases.
Contribute to standards, guidelines, and documentation for ML practices.
Communicate status, risks, and progress to leadership and cross-functional teams.
Minimum Qualifications: Master's degree in Computer Science, Software Engineering, Data Science, Machine Learning, Mathematics, Physics, or a related field; or equivalent relevant experience.
5+ years of software development in a cloud environment.
3+ years building large-scale ML/DL models, from POC to production.
Hands-on experience with one or more DL frameworks (e.g.,PyTorch, TensorFlow).
Experience with cloud data platforms (AWS, Azure, GCP) and data/ML tooling (e.g., Databricks,MLFlow,Streamlit).
Proficiencyin ETL, feature engineering, datavisualization.
Experience operating high-availability, fault-tolerant, scalable distributed systems withGitOpspractices (Terraform preferred).
Familiarity with stream processing (ksqlDB, Spark Streaming, Beam/Flink) and modern ML deployment patterns.
Strong programming skills in Python, Java/Scala, and/orGo;fluency in clean, maintainable code.
Excellent analytical, critical thinking, and problem-solving abilities.
Effective written and verbal communication; comfortable explaining technical concepts to non-experts and senior leadership.
Ability to thrive in a fast-paced, collaborative environment.
Experience guiding junior engineers and providing technical leadership.
Preferred Qualifications PhD in a related field.
Experience with Databricks and a broad range of ML tooling.
Equivalents and Substitutions Equivalent relevant experience may substitute for degree requirements (1 year of experience per year of education at the discretion of the Hiring Manager).
#LI-GB1 Position & Application Details Full-Time Regular Positions (classified as regular and working 40 standard weekly hours): This is a full-time, regular position (classified for 40 standard weekly hours) 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.
How to Apply: If interested, an application will need to be submitted online. Internal WGU employees will need to apply through the internal job board in Workday. Additional Information Disclaimer: The job posting highlights the most critical responsibilities and requirements of the job. It's not all-inclusive. Accommodations: Applicants with disabilities who require assistance or accommodation during the application or interview process should contact our Talent Acquisition team at recruiting@wgu.edu. Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to any protected characteristic as required by law. Required
Preferred
Job Industries
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Compétences linguistiques
- English
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