Generative AI developer (experience 1 to 2 years) Early-career AI/ML Engineer supporting the development and deployment of Generative AI solutions (LLMs, RAG systems). Focus on hands-on implementation, integration, and learning-by-delivery, under guidance.
Must Have:
- Strong foundation in Python (data handling, APIs, scripts)
- Understanding of APIs, Docker, or deployment workflows
- Exposure to deploying ML/AI models (even in projects/internships)
- Understanding of embeddings, retrieval flow
- Hands-on exposure through projects
- Experience working with GPT/Llama APIsAbility to structure prompts and evaluate outputs
- Vector Databases (Exposure Level)
- Familiarity with FAISS / Chroma / Pinecone and basic usage in projects.ML Fundamentals: Core concepts - overfitting, evaluation metrics, basic algorithms.
- Ability to reason about model behavior.
Core Responsibilities
- (Execution Under Guidance)
- Assist in building RAG-based Gen
- AI solutions for enterprise use cases.
- Develop Python-based services/APIs integrating LLMs.
- Support data preprocessing, embeddings, and retrieval pipelines.
- Contribute to model deployment and integration tasks.
- Debug and improve existing pipelines under supervision.
- Work closely with senior engineers to understand production constraints (latency, cost, accuracy)
- Good to Have
- Lang
- Chain / Llama
- Index exposure
- Cloud basics (Azure / AWS / GCP)
- Basic understanding of CI/CD or MLOps concepts
- Internship/project experience in Gen
- AI or ML use cases Must Have:
- Strong foundation in Python (data handling, APIs, scripts)
- Understanding of APIs, Docker, or deployment workflows
- Exposure to deploying ML/AI models (even in projects/internships)
- Understanding of embeddings, retrieval flow
- Hands-on exposure through projects
- Experience working with GPT/Llama APIsAbility to structure prompts and evaluate outputs
- Vector Databases (Exposure Level)
- Familiarity with FAISS / Chroma / Pinecone and basic usage in projects.ML Fundamentals: Core concepts - overfitting, evaluation metrics, basic algorithms.
- Ability to reason about model behavior.
Core Responsibilities
- (Execution Under Guidance)
- Assist in building RAG-based Gen
- AI solutions for enterprise use cases.
- Develop Python-based services/APIs integrating LLMs.
- Support data preprocessing, embeddings, and retrieval pipelines.
- Contribute to model deployment and integration tasks.
- Debug and improve existing pipelines under supervision.
- Work closely with senior engineers to understand production constraints (latency, cost, accuracy)
- Good to Have
- Lang
- Chain / Llama
- Index exposure
- Cloud basics (Azure / AWS / GCP)
- Basic understanding of CI/CD or MLOps concepts
- Internship/project experience in Gen
- AI or ML use cases
- Experience & Qualification
- Bachelor's in Computer Science / Data Science or related field.12 years of experience in AI/ML (including internships and project work).
- Exposure to at least one end-to-end ML/Gen
- AI project (academic and professional).
