AI–ML Engineer (Lead)

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, Next.js) 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.