Senior Machine Learning Engineer
United States of America
Full Time
2 weeks ago
$157,000 - $243,000 USD
H1B Sponsor Likely
Key skills
PythonJavaGoScalaAIMachine LearningMLNLPLLMPyTorchTensorFlowMLOpsMLflowETLData EngineeringDatabricksSparkAWSAzureGCPTerraformGitOpsLeadershipCommunicationCritical ThinkingCollaboration
About this role
Western Governors University is dedicated to expanding access to higher education through innovative online programs. They are seeking a Senior Machine Learning Engineer to build and deploy advanced NLP/LLM models, mentor junior engineers, and collaborate with cross-functional teams to enhance student learning experiences.
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 technical lead on complex ML projects
- Model research, development, and deployment
- Research and prototype state-of-the-art NLP/LLM techniques; evaluate and select approaches suitable for production
- Develop, train, fine-tune, and optimize production-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 with MLOps to 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 to validate outcomes
- 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
Requirements:
- 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)
- Proficiency in ETL, feature engineering, data visualization
- Experience operating high-availability, fault-tolerant, scalable distributed systems with GitOps practices (Terraform preferred)
- Familiarity with stream processing (ksqlDB, Spark Streaming, Beam/Flink) and modern ML deployment patterns
- Strong programming skills in Python, Java/Scala, and/or Go; 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
- PhD in a related field
- Experience with Databricks and a broad range of ML tooling