We are looking for an MLOps Engineer with robust experience in deploying, scaling, and monitoring machine learning models in production environments. This role focuses on building reliable ML pipelines, optimizing model inference performance, and ensuring end-to-end lifecycle management of ML systems.

What you’ll be Responsible for?
Build, deploy, and scale ML models using Docker and Kubernetes (EKS/AKS).
Develop and manage CI/CD pipelines using GitHub Actions / Jenkins.
Design and maintain low-latency, high-throughput REST/gRPC services for ML model serving.
Implement model serving and inference using vLLM, Triton Inference Server, or TGI.
Optimize inference performance by tuning batch sizes, managing GPU memory, and improving throughput.
Implement logging of prompt/response pairs, monitor model performance, and detect model drift.
Set up monitoring and observability using LangFuse, Helicone, or similar tools.
Build and manage ML pipelines and experiment tracking using MLflow or Weights & Biases.
Develop automated retraining pipelines and manage model versioning and registry.




Build and maintain data pipelines for training data ingestion, PII handling, and versioning using DVC.
Work with data storage systems like ClickHouse or similar columnar databases.
What you’d have?
4–6 years of experience in MLOps / ML Engineering roles.
Strong programming skills in Python (mandatory) and working knowledge of Bash.
Hands-on experience with Kubernetes, Docker, and CI/CD pipelines.
Experience in building and scaling REST/gRPC APIs and services.
Robust understanding of system design for high-performance, scalable systems.
Experience with Git-based version control workflows.
Hands-on experience with model serving tools (vLLM, Triton, TGI).
Strong understanding of ML lifecycle, model monitoring, and observability.
Experience with experiment tracking tools (MLflow or Weights & Biases).
Basic data engineering knowledge including data pipelines and versioning.
Solid problem-solving

📌 Mlops Engineer Hyderabad
🏢 Tanla Platforms
📍 Hyderabad