• Develop and optimize RAG pipelines: document chunking, embedding generation, vector storage, retrieval, reranking, and grounded generation with citations
• Work on LLM-based applications: fine-tuning open-source models (LLaMA, Mistral, etc), building prompt strategies, and deploying inference services
• Contribute to machine learning models (classification, regression, recommendation, anomaly detection) and deep learning architectures (CNNs, RNNs, Transformers)
• Implement robust model evaluation frameworks (accuracy, F1, BLEU, perplexity, hallucination detection, relevance)
• Collaborate with senior engineers on scalable pipelines, guardrails, and integration with enterprise systems

• Programming & Foundations
• Strong in Python, data structures, and algorithms
• Hands-on with NumPy, Pandas, Scikit-learn for ML prototyping
• Machine Learning
• Understanding of supervised/unsupervised learning, regularization, feature engineering, model selection, cross-validation, ensemble methods (XGBoost, LightGBM)
• Deep Learning
• Proficiency with PyTorch (preferred) or TensorFlow/Keras
• Knowledge of CNNs, RNNs, LSTMs, Transformers, Attention mechanisms
• Familiarity with optimization (Adam, SGD), dropout, batch norm
• LLMs & RAG
• Hugging Face Transformers (tokenizers, embeddings, model fine-tuning)
• Vector databases (Milvus, FAISS, Pinecone, ElasticSearch)
• Prompt engineering, function/tool calling, JSON schema outputs
• Data & Tools
• SQL fundamentals; exposure to data wrangling and pipelines
• Git/GitHub, Jupyter, basic Docker

• Built a personal ML/LLM project (chatbot, RAG app, document Q&A, finetuned model)
• Familiarity with LangChain/LlamaIndex/Agno frameworks
• Knowledge of cloud platforms (Azure/AWS/GCP) and MLOps basics (CI/CD, MLflow, W&B)
• Exposure to knowledge graphs or multi-agent workflows

What Were Looking For

• Solid academic foundation with strong applied ML/DL exposure.
• Curiosity to learn cutting-edge AI and willingness to experiment.
• Clear communicator who can explain ML/LLM trade-offs simply.
• Strong problem-solving and ownership mindset.

Minimum Qualifications

• Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years

Swing Shift:2-11 pm