Machine Learning Ops Engineer
2 days ago
About the Role
We are seeking a Machine Learning Ops Engineer to support and scale our ML/AI infrastructure. The role involves working with LangServe, LangFuse, Docker, and Kubernetes to deploy, monitor, and optimize ML models in production environments.
Key Responsibilities
• Assist in designing and managing ML model deployment pipelines.
• Work with LangServe to deploy and serve ML/LLM applications.
• Implement monitoring and logging using LangFuse for model performance tracking.
• Containerize ML applications with Docker and deploy them on Kubernetes clusters.
• Collaborate with Data Scientists to integrate ML models into production systems.
• Support CI/CD pipelines for model updates and versioning.
• Ensure system reliability, scalability, and automation for ML workloads.
Required Skills
• 24 years of experience in ML Ops
• Hands-on experience with LangServe and LangFuse.
• Good understanding of Docker (building images, managing containers).
• Exposure to Kubernetes (deployment, scaling, Helm, monitoring).
• Programming skills in Python (preferred) or Java.
• Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Understanding of CI/CD tools (GitHub Actions, Jenkins, etc.).
• Basic knowledge of cloud platforms (AWS / GCP / Azure).
Good to Have
• Exposure to LangChain or RAG pipelines.
• Knowledge of observability tools (Prometheus, Grafana, ELK).
• Understanding of ML lifecycle management (MLflow, DVC).
Educational Qualification
• Bachelors degree in Computer Science, Data Science, AI/ML, or related field.
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