Job
Description
We are looking for a technically adept and instructionally strong AI Developer with core expertise in Python, Large Language Models (LLMs), prompt engineering, and vector search frameworks such as FAISS, LlamaIndex, or RAG-based architectures. The ideal candidate combines solid foundations in data science, statistics, and machine learning development with a hands-on understanding of ML DevOps, model selection, and deployment pipelines. 3–4 years of experience in applied machine learning or AI development, including at least 1–2 years working with LLMs, prompt engineering, or vector search systems. Core Skills Required Python: Advanced-level expertise in scripting, data manipulation, and model development LLMs (Large Language Models): Practical experience with GPT, LLaMA, Mistral, or open- source transformer models Prompt Engineering: Ability to design, optimize, and instruct on prompt patterns for various use cases Vector Search & RAG: Understanding of feature vectors, nearest neighbor search, and retrieval-augmented generation (RAG) using tools like FAISS, Pinecone, Chroma, or Weaviate LlamaIndex: Experience building AI applications using LlamaIndex, including indexing documents and building query pipelines Rack Knowledge: Familiarity with RACK architecture, model placement, and scaling on distributed hardware ML / ML DevOps: Knowledge of full ML lifecycle including feature engineering, model selection, training, and deployment Data Science & Statistics: Solid grounding in statistical modeling, hypothesis testing, probability, and computing concepts Responsibilities Design and develop AI pipelines using LLMs and traditional ML models Build, fine-tune, and evaluate large language models for various NLP tasks Design prompts and RAG-based systems to optimize output relevance and factual grounding Implement and deploy vector search systems integrated with document knowledge bases Select appropriate models based on data and business requirements Perform data wrangling, feature extraction, and model training Develop training material, internal documentation, and course content (especially around Python and AI development using LlamaIndex) Work with DevOps to deploy AI solutions efficiently using containers, CI/CD, and cloud infrastructure Collaborate with data scientists and stakeholders to build scalable, interpretable solutions Maintain awareness of emerging tools and practices in AI and ML ecosystems Preferred Tools & Stack Languages: Python, SQL ML Frameworks: Scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers Vector DBs: FAISS, Pinecone, Chroma, Weaviate RAG Tools: LlamaIndex, LangChain ML Ops: MLflow, DVC, Docker, Kubernetes, GitHub Actions Data Tools: Pandas, NumPy, Jupyter Visualization: Matplotlib, Seaborn, Streamlit Cloud: AWS/GCP/Azure (S3, Lambda, Vertex AI, SageMaker) Ideal Candidate Background in Data Science, Statistics, or Computing Passionate about emerging AI tech, LLMs, and real-world applications Demonstrates both hands-on coding skills and teaching/instructional abilities Capable of building reusable, explainable AI solutions Location gurgaon sector 49 APPLY NOW
