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...