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AI Engineer – ML, LLM & Agentic AI
Ecolibrium
Karnataka, IND
Full-time
Mid-Senior
Onsite
Discovered 1 weeks ago
Machine learningDeep learningLLMsGenerative AIAgentic AIPython
Free
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Machine learningDeep learningLLMs
Role Overview
Build intelligent systems end to end across machine learning, LLMs, generative AI, agentic AI, model development, fine-tuning, and production AI systems.
Take ambiguous problems from AI approach selection through solution development, evaluation, productionization, and continuous improvement.
This is a hands-on individual contributor role requiring strong AI fundamentals and production engineering discipline.
Key Skills for This Role
Machine learningDeep learningLLMsGenerative AIAgentic AIPython
Full Job Posting
Role Overview
Build intelligent systems end to end across machine learning, LLMs, generative AI, agentic AI, model development, fine-tuning, and production AI systems.
Take ambiguous problems from AI approach selection through solution development, evaluation, productionization, and continuous improvement.
This is a hands-on individual contributor role requiring strong AI fundamentals and production engineering discipline.
AI and ML Engineering
- Own AI initiatives from problem definition and experimentation through development, evaluation, production, and continuous improvement.
- Translate product problems into measurable AI or ML solutions and select ML, LLM, RAG, fine-tuning, agentic AI, or hybrid approaches.
- Build, train, evaluate, and deploy ML models using modern frameworks such as PyTorch, TensorFlow, and scikit-learn.
- Build evaluation frameworks for ML and LLM systems and optimize quality, latency, cost, and reliability.
LLM and Agentic AI Systems
- Build production-grade LLM applications, intelligent workflows, and agentic AI systems with planning, reasoning, tool use, and multi-step execution.
- Build RAG pipelines, retrieval systems, embeddings, and semantic search using vector stores such as pgvector, Qdrant, Milvus, or Pinecone.
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