Sr. Machine Learning Engineer

4+ years of hands-on experience in building and deploying ML models in production. Strong proficiency in Python and ML Frameworks (PyTorch, LangChain, Agents). Experience with AWS Cloud, Kubernetes, ArgoCD, Docker, Terraform, Jenkins and CI/CD pipelines. Experience with monitoring ML models using Datadog and/or OpenSearch. Experience building ML services using Python web frameworks (FastAPI) or stream processing libraries (Faust). Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative AI. Ability to collaborate with cross-functional teams and communicate technical concepts. Familiarity with Enterprise RAG Systems.

Build and deploy scalable ML solutions using Docker, Kubernetes, MLflow, Kafka, and AWS Services. Leverage vector databases and streaming systems for real-time data processing. Standardize ML workflows using MLflow. Automate and orchestrate ML workflows using tools like Airflow. Optimize ML pipelines and leverage cloud services like AWS. Develop cutting-edge generative AI capabilities using LLMs. Evaluate generative AI applications and build automated evaluation pipelines. Collaborate with cross-functional teams. Stay updated on emerging ML trends and best practices.