We are seeking an AI/ML Engineer with strong hands-on experience in machine learning, LLMs, NLP, data processing, and model deployment. The ideal candidate should be capable of building clean, scalable AI architectures, designing agentic workflows, fine-tuning models, preparing datasets, and integrating LLMs into production applications.
You will own end-to-end AI execution while staying current with evolving AI/LLM advancements.
Location: Coimbatore (Work From Office)
Model Development & Fine-Tuning
- Build, train, and fine-tune ML/NLP/LLM models for production use.
- Evaluate performance using standard AI metrics and deliver measurable improvements.
- Optimize models for accuracy, latency, and scalability.
AI Architecture & System Design
- Design clean, modular, and scalable AI pipelines (data → training → evaluation → inference).
- Implement production-ready inference services and APIs.
- Ensure system design supports high-quality, maintainable, and extensible AI workflows.
Prompt Engineering & LLM Integration
- Create and optimize prompts, structured reasoning, and multi-step chains.
- Integrate LLMs (OpenAI, Azure, Hugging Face, etc.) into applications.
- Evaluate LLM outputs for quality, stability, and reduced hallucinations.
Agentic Workflow Development
- Build and orchestrate agent-based AI workflows.
- Connect LLM agents with tools, APIs, memory, and multi-step reasoning flows.
- Improve autonomy, adaptability, and decision-making accuracy within agentic systems.
Dataset Preparation & Validation
- Prepare, clean, label, and validate datasets for ML/LLM training and evaluation.
- Identify data bias, duplications, and quality issues.
- Build evaluation datasets aligned with product and QA expectations.
Deployment & Integration
- Develop inference pipelines and microservices for real-time and batch predictions.
- Implement versioning, monitoring, and logging for model lifecycle maintenance.
- Collaborate with engineering teams for seamless integration.
Research & Innovation
- Stay updated with advancements in LLMs, embeddings, vector search, and generative AI.
- Evaluate and apply new architectures, frameworks, and techniques to enhance product capabilities.
Documentation & Collaboration
- Document model architecture, datasets, experiments, workflows, and deployment processes.
- Work with Product, QA, and Engineering to define AI evaluation criteria and expectations.
- Participate in sprint ceremonies and cross-functional planning sessions.
Bachelor’s degree in Computer Science, Data Science, AI/ML, or related field.
2–3 years of experience in ML/AI model development and deployment.
Strong Python skills (PyTorch/TensorFlow, Hugging Face, Scikit-learn, NumPy, Pandas).
Experience fine-tuning and integrating NLP/LLM models.
Strong understanding of embeddings, vector search, and evaluation metrics.
Experience building REST APIs and inference pipelines.
Knowledge of cloud platforms (Azure/AWS/GCP).
Ability to design clean, scalable ML/LLM system architectures.
Excellent analytical thinking and communication skills.
* Experience with vector databases (FAISS, Pinecone, ChromaDB).
* Experience with agentic frameworks and orchestration tools (LangChain, LlamaIndex, Semantic Kernel, etc.).
* Understanding of MLOps and CI/CD for ML systems.
* Exposure to healthcare or AI-driven SaaS products.