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AI/ML Engineer
Agilisium
Chennai, IND
Full-time
Mid · 2+ years experience
Onsite
Discovered 3 weeks ago
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Full Job Posting
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 .
- Apply 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 .
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