Quick overview
Job description
Job Profile:
An expert Prompt engineer with a strong software engineering a background and an excellent communicator with 8+ years of experience implementing AI and ML use cases. (Primarily AI)
Knowledge of Computer vision related projects.
LLM Expertise:
- Must have hands-on experience working with modern LLMs (OpenAI, Anthropic, LLaMA, Mistral, Gemini),as well as a strong understanding of tokenization, model behaviors, reasoning patterns, and evaluation frameworks.
- Prompt Design & Optimization (zero-shot, few-shot, chain-of-thought, ReAct, self-consistency)
- Structured prompt templates
- Refinement (prompt chaining, decomposition, and verification strategies)
- Safety, Guardrails & Compliance
- Experience building conversational flows (chatbots).
Retrieval-Augmented Generation (RAG) :
- Work with embedding models, vector databases, context windows, and chunking strategies
- Work experience in Vector database (FAISS, Milvus, Pinecone or any)
Machine Learning:
- Machine Learning Engineer with strong experience in building, deploying, and optimizing end-to-end ML systems.
- Skilled in data preprocessing, feature engineering, model development, and production deployment using modern ML frameworks.
- Proficient in Python, PyTorch/ TensorFlow, cloud services, and MLOps practices.
Software Engineering:
- Python proficiency.
- Very good understanding and work experience with REST APIs, JSON, YAML.
- Ability to integrate LLM prompts into production applications.
- Familiarity with Git, version control, and experiment tracking.
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