Senior Machine Learning Engineer
WGU North Carolina, United States
USD 157K-243K Senior-level Full Time
Tasks
- Apply NLP insights to unstructured data sources
- Build data processing pipelines with training inference data
- Communicate status risks and progress to leadership
- Create standards guidelines and documentation for ML practices
- Define NLP initiatives roadmaps and success metrics
- Deploy ML models with performance scalability reliability and observability
- Develop train fine tune and optimize NLP LLM models
- Ensure scalable reproducible deployment monitoring and model governance
- Integrate ML solutions with software infrastructure and security
- Mentor junior engineers and lead complex ML projects
- Research prototype and evaluate NLP LLM techniques for production
- Stay current with NLP LLM DL and AI trends
- Translate business requirements into NLP capabilities
Perks/Benefits
- Bonuses
- Dental insurance
- Disability coverage
- Discounted tuition
- Flexible paid time off
- Flexible spending account
- Health insurance
- Health savings account
- Life insurance
- Mental health coverage
- Paid Holidays
- Parental leave
- Retirement savings plan
- Telehealth
- Vision insurance
- Wellbeing program
Skills/Tech-stack
AWS | Apache Beam | Apache Kafka | Azure | Cloud platform | Data Governance | Data Visualization | Databricks | Distributed Systems | ETL | Fault-tolerant | Fault-tolerant systems | Feature Engineering | Fine Tuning | Flink | GitOps | Go | Google Cloud | Google Cloud Platform | High Availability | High-availability systems | Java | Kubernetes | MLflow | Model Deployment | Model Monitoring | PyTorch | Python | Scala | Security | Spark Streaming | Streamlit | TensorFlow | Terraform
Education
Bachelor of Science | Master of Engineering | Master of Science
Regions
Countries
States
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