F2F Walkin Drive - 14th Feb 2026
Location: Hyderabad

Accountabilities:
Design, develop, train, and deploy production-grade ML and GenAI models across use cases including NLP, computer vision, and structured data modeling.
Leverage frameworks such as TensorFlow, Keras, PyTorch, and LangChain to build scalable deep learning and LLM-based solutions.
Develop and maintain end-to-end ML pipelines with reusable, modular components for data ingestion, feature engineering, model training, and deployment.
Implement and manage models on cloud platforms such as AWS, GCP, or Azure using services like SageMaker, Vertex AI, or Azure ML.
MLOps best practices using tools like MLflow, Kubeflow, Weights & Biases, Airflow, DVC, and Prefect to ensure scalable and reliable ML delivery.
Incorporate CI/CD pipelines (using Jenkins, GitHub Actions, or similar) to automate testing, packaging, and deployment of ML workloads.
Containerize applications using Docker and orchestrate scalable deployments via Kubernetes.
Integrate LLMs with APIs and external systems using LangChain,



Vector Databases (e.g., FAISS, Pinecone), and prompt engineering best practices.
Collaborate closely with data engineers to access, prepare, and transform large-scale structured and unstructured datasets for ML pipelines.
Build monitoring and retraining workflows to ensure models remain performant and robust in production.
Evaluate and integrate third-party GenAI APIs or foundational models where appropriate to accelerate delivery.
Maintain rigorous experiment tracking, hyper parameter tuning, and model versioning.
Champion industry standards and evolving practices in ML lifecycle management, cloud-native AI architectures, and responsible AI.
Work across global, multi-functional teams, including architects, principal engineers, and domain experts.

Essential Skills / Experience:
2–10 years of hands-on experience in developing, training, and deploying ML/DL/GenAI models.
Robust programming

📌 Ai/ml Engineer Chennai
🏢 Agilisium
📍 Chennai