Ai Ml Engineer

Role & responsibilities

• Build, train, evaluate, and deploy predictive machine learning models.
• Design and develop LLM-powered applications and intelligent AI agents.
• Build and implement Retrieval-Augmented Generation (RAG) pipelines.
• Fine-tune Large Language Models using techniques.
• Perform feature engineering, data preprocessing, model training, and performance evaluation.
• Work with vector databases for efficient document retrieval and semantic search.
• Design and develop multi-step agent workflows for complex problem-solving.
• Integrate AI solutions with APIs, applications, and business workflows.
• Optimize AI/ML models and applications for scalability, accuracy, and performance.
• Collaborate with cross-functional teams including software developers, data engineers, product teams, and business stakeholders.
• Stay updated with emerging technologies and best practices in Machine Learning, Generative AI, LLMs, and agent-based systems.

Mandatory Technical Skills

Programming & Machine Learning

• Expert-level proficiency in Python.
• Strong working knowledge of SQL.
• Hands-on experience with Scikit-learn, XGBoost, and LightGBM.
• Experience with Pandas and NumPy.
• Strong understanding of feature engineering, data preprocessing, and model evaluation.
• Good knowledge of evaluation metrics such as F1 Score, AUC-ROC, Precision, Recall, and Precision-Recall.

Deep Learning & LLMs

• Hands-on experience with PyTorch or TensorFlow.
• Strong experience with Hugging Face Transformers.
• Experience building applications using OpenAI and Anthropic APIs.
• Hands-on experience with LangChain and/or LlamaIndex.
• Practical experience in LLM fine-tuning, including LoRA, QLoRA, and PEFT.

RAG & Vector Databases

• Strong hands-on experience building RAG pipelines.

• Experience working with vector databases such as:

• Pinecone

• Milvus

• Weaviate

• Understanding of document retrieval, embeddings, chunking, and semantic search.

AI Agents

• Experience developing autonomous or intelligent agents using frameworks such as:

• LangChain

• CrewAI

• AutoGPT

• Experience designing agents for multi-step problem-solving and workflow automation.