AI/ML Engineer (LLM & Agent Systems)

We are looking for skilled and experienced AI/ML Engineers with hands-on expertise in predictive modeling, Machine Learning, Large Language Models (LLMs), Generative AI, RAG pipelines, and agent-based systems. The ideal candidate should be capable of designing, developing, deploying, and optimizing scalable AI solutions for real-world business use cases. The role requires strong programming skills, practical experience with modern ML frameworks, and hands-on exposure to LLM fine-tuning and intelligent agent workflows.

• • 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 PEFT, LoRA, and QLoRA 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.

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or a related field.

• 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:
• o Pinecone
• o Milvus
• o Weaviate
• • Understanding of document retrieval, embeddings, chunking, and semantic search.
• AI Agents
• • Experience developing autonomous or intelligent agents using frameworks such as:
• o LangChain
• o CrewAI
• o AutoGPT
• • Experience designing agents for multi-step problem-solving and workflow automation.

• • Experience with Docker and Kubernetes.
• • Knowledge of Apache Spark.
• • Experience with Weights & Biases or similar tools for experiment tracking.
• • Experience in data curation and tokenization.
• • Experience deploying and monitoring AI/ML models in production environments.
• • Familiarity with cloud-based AI/ML services and scalable deployment architectures.