
AI–ML Engineer
2 days ago
Job Title: AI–ML Engineer
Experience: 2–3 Years
Work Mode: Onsite
Location: Kinfra Film and IT Park, Trivandrum
Preferred Candidates: From Kerala
Employment Type: Full-time
Salary: Best in the Industry + Insurance
About the Role
We are looking for a skilled AI–ML Engineer with 2–3 years of hands-on experience in Agentic AI, Generative AI, MLOps, LLMs, and RAG-based systems. The ideal candidate is someone who can independently build, deploy, and optimize AI-driven products and solutions—working across both front-end and back-end development environments with cloud deployment expertise on Azure or AWS.
Key Responsibilities
- AI Product Development: Build and deploy end-to-end AI products integrating data pipelines, APIs, and user-facing components.
- LLM & RAG Solutions: Implement and fine-tune Large Language Models and Retrieval-Augmented Generation systems for real-world applications.
- Agentic AI Development: Design and develop AI agents capable of reasoning, planning, and executing tasks autonomously.
- Generative AI Applications: Work with text, image, and multimodal generation models to build next-generation AI tools.
- MLOps Implementation: Set up CI/CD pipelines, manage model lifecycle, and ensure reproducibility and performance at scale.
- Cloud Deployment: Deploy and monitor models and APIs on Azure or AWS, ensuring high availability, scalability, and security.
- Collaboration: Partner with data scientists, developers, and product managers to deliver robust, business-aligned AI solutions.
Required Skills & Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
- 2–3 years of experience in AI/ML engineering or applied AI product development.
- Proficiency in Python, frameworks like PyTorch / TensorFlow, and API frameworks (FastAPI, Flask).
- Experience in LLM fine-tuning, RAG pipelines, and vector databases (FAISS, Pinecone, ChromaDB, etc.).
- Knowledge of MLOps tools (MLflow, Kubeflow, DVC) and containerization (Docker, Kubernetes).
- Experience deploying AI applications on Azure Machine Learning or AWS SageMaker.
- Exposure to front-end integration (React, ) is an added advantage.
Preferred Skills
- Experience with LangChain, LlamaIndex, or similar frameworks for building AI agents.
- Familiarity with prompt engineering, API integration, and microservices.
- Understanding of cloud-native AI design patterns and generative AI evaluation methods.
Why Join Us
- Be part of cutting-edge AI projects using LLMs, RAG, and Agentic AI.
- Opportunity to lead full-cycle AI product development—concept to deployment.
- Collaborative and innovation-driven culture with continuous learning.
- Competitive compensation with growth opportunities in a fast-evolving AI domain.
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