Job Description
Role & Responsibilities
Design and implement classic ML models (XGBoost, SVMs, clustering, etc.) for structured data use cases.
Build and optimize deep learning pipelines using PyTorch/TensorFlow, with a focus on NLP and multimodal tasks.
Develop modern AI systems , including RAG-based applications leveraging LangChain, LlamaIndex, and vector databases (FAISS, Weaviate).
Architect and experiment with agentic AI systems featuring tool usage, memory, planning, and self-reflection (CrewAI, LangGraph, AutoGen).
Deploy ML models in production environments using Docker, MLflow, Ray, or Kubernetes.
Preferred Candidate Profile
3–5 years of experience in software or ML engineering.
Strong proficiency in Python , with hands-on experience in ML model building.
Exposure to open-source LLMs (e.g., LLaMA, Mistral, Falcon).
Bonus: Experience in fine-tuning LLMs or building autonomous AI agents .
Key Attributes
Strong problem-solving and analytical ski...
Design and implement classic ML models (XGBoost, SVMs, clustering, etc.) for structured data use cases.
Build and optimize deep learning pipelines using PyTorch/TensorFlow, with a focus on NLP and multimodal tasks.
Develop modern AI systems , including RAG-based applications leveraging LangChain, LlamaIndex, and vector databases (FAISS, Weaviate).
Architect and experiment with agentic AI systems featuring tool usage, memory, planning, and self-reflection (CrewAI, LangGraph, AutoGen).
Deploy ML models in production environments using Docker, MLflow, Ray, or Kubernetes.
Preferred Candidate Profile
3–5 years of experience in software or ML engineering.
Strong proficiency in Python , with hands-on experience in ML model building.
Exposure to open-source LLMs (e.g., LLaMA, Mistral, Falcon).
Bonus: Experience in fine-tuning LLMs or building autonomous AI agents .
Key Attributes
Strong problem-solving and analytical ski...
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