Machine Learning Engineer (AI Systems)

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 ...