Associate Machine Learning Engineer
Tasks
- Build and maintain MLOps pipelines for ingestion feature engineering training deployment and monitoring
- Collaborate with data scientists to develop train and evaluate machine learning models
- Create and maintain documentation for architecture design deployment disaster recovery and operations
- Develop and deploy ML models on AWS and Databricks
- Develop and execute unit and integration tests
- Evaluate model performance using metrics and optimize for accuracy and efficiency
- Implement DevSecOps practices for secure scalable and reliable solutions
- Monitor AI and LLM systems for availability latency error rates and quality degradation
- Participate in incident triaging root cause analysis and mitigation actions
- Provide support and maintenance for production applications
- Version models prompts and pipelines across development test and production
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agile | Airflow | Apache Hadoop | Apache Spark | Big Data | Databricks | DevSecOps | Docker | Grafana | Integration Testing | Kubeflow | Kubernetes | Langchain | MLOps | MLflow | Machine Learning | Model Explainability | Model Monitoring | Model Observability | Prometheus | Prompt engineering | PyTorch | Python | RAG | Retrieval-Augmented Generation | Scikit-learn | Semantic Kernel | Splunk | TensorFlow | Unit Testing | Vector Database
Education
N/A
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