Machine Learning Engineer LLM / MLOps
Job Title: Machine Learning Engineer LLM & MLOps
Location: Remote (U.S.)
Employment Type: Full-Time
About the Opportunity:
An exciting role for an ML Engineer to build scalable ML systems deploy models and work with cutting-edge AI technologies including LLMs and RAG architectures.
Key Responsibilities:
- Build train and deploy ML models at scale
- Develop reusable pipelines using Databricks and MLflow
- Implement CI/CD workflows for ML deployment
- Work with LLMs RAG and AI agent frameworks
- Monitor model performance drift and retraining cycles
Required Skills:
- 5 years of ML Engineering experience
- Strong Python programming and ML frameworks (PyTorch TensorFlow Scikit-learn)
- Hands-on experience with Databricks MLflow PySpark
- Experience with AWS (S3 SageMaker Lambda etc.)
- Strong understanding of MLOps and model lifecycle
Preferred:
- Experience building AI-driven applications (Streamlit Gradio)
- Strong system design and data pipeline experience
- Business understanding of AI applications
Clearance: Public Trust (or eligible)
Hashtags:
#MLEngineer #MachineLearning #MLOps #LLM #AWS #Databricks #PySpark #AIEngineering #RemoteJobs #HiringNow
Machine Learning Engineer LLM / MLOps Job Title: Machine Learning Engineer LLM & MLOps Location: Remote (U.S.) Employment Type: Full-Time About the Opportunity: An exciting role for an ML Engineer to build scalable ML systems deploy models and work with cutting-edge AI technologies including...
Machine Learning Engineer LLM / MLOps
Job Title: Machine Learning Engineer LLM & MLOps
Location: Remote (U.S.)
Employment Type: Full-Time
About the Opportunity:
An exciting role for an ML Engineer to build scalable ML systems deploy models and work with cutting-edge AI technologies including LLMs and RAG architectures.
Key Responsibilities:
- Build train and deploy ML models at scale
- Develop reusable pipelines using Databricks and MLflow
- Implement CI/CD workflows for ML deployment
- Work with LLMs RAG and AI agent frameworks
- Monitor model performance drift and retraining cycles
Required Skills:
- 5 years of ML Engineering experience
- Strong Python programming and ML frameworks (PyTorch TensorFlow Scikit-learn)
- Hands-on experience with Databricks MLflow PySpark
- Experience with AWS (S3 SageMaker Lambda etc.)
- Strong understanding of MLOps and model lifecycle
Preferred:
- Experience building AI-driven applications (Streamlit Gradio)
- Strong system design and data pipeline experience
- Business understanding of AI applications
Clearance: Public Trust (or eligible)
Hashtags:
#MLEngineer #MachineLearning #MLOps #LLM #AWS #Databricks #PySpark #AIEngineering #RemoteJobs #HiringNow
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