Associate Machine Learning Engineer
Tasks
- Build and maintain MLOps pipelines
- Collaborate with data scientists to train and evaluate machine learning models
- Create and maintain unit tests integration tests and testing strategies
- Develop and deploy machine learning models on cloud platforms
- Develop and maintain software and deployment documentation
- Evaluate model performance and optimize accuracy and efficiency
- Execute LLM evaluation runs for reliability safety and grounding
- Implement DevSecOps practices for secure ML services
- Monitor ML and LLM systems for availability latency and error rates
- Operate AI services and perform incident triage root cause analysis and rollback
- Version models prompts and pipelines across environments
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Airflow | Apache Spark | Docker | Grafana | Hadoop | Kubeflow | Kubernetes | Langchain | Large Language Model | Large language model inference | Logging | MLOps | MLflow | Machine Learning | Model Explainability | Model Inference | Model Monitoring | Model Observability | Performance Tuning | Prometheus | Prompt engineering | PyTorch | Python | RAG | Retrieval-Augmented Generation | Scikit-learn | Semantic Kernel | Splunk | TensorFlow | Vector Database
Education
N/A
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