Roles & Responsibilities

AI/ML Development: Design, develop, and deploy production-grade AI/ML and Generative AI solutions.

Search Optimization: Work on GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), and SGE (Search Generative Experience) initiatives to improve visibility and discoverability across AI-driven search and generative interfaces.

Content & Data Optimization: Optimize content, data, and digital experiences for AI-powered search, conversational queries, and LLM-based experiences.

Advanced Tech Stack: Develop solutions using LLMs, NLP, semantic search, embeddings, RAG (Retrieval-Augmented Generation), and vector databases.

Data Analysis: Analyze search intent, AI-generated responses, retrieval patterns, citations, and content discoverability to identify optimization opportunities.

Experimentation: Build experiments and frameworks to measure the effectiveness of GEO/AEO strategies and AI search performance.

Cross-functional Collaboration: Collaborate with Product, Engineering, Content, SEO, Marketing, and Business teams to translate business requirements into scalable AI solutions.

Performance Monitoring: Monitor model and solution performance and continuously improve accuracy, relevance, latency, and overall user experience.

Ideal Candidate Requirements

Education (Mandatory): B.Tech or Dual degree (B.Tech M.Tech or Integrated MSc/MS)





strictly from Tier 1 Engineering Institutes (IITs, NITs, VIT, BITS, DTU, NSUT).

LOCATION

Pune (In-Office)

EXPERIENCE

1 - 4 Years

WORKING DAYS

5 Days

NOTICE PERIOD

Max 30 Days

Company Pedigree (Mandatory): Must be currently/previously working in top product companies operating at a high scale. (Tier 2 companies will not be considered).

Rank Modeling (Mandatory): Must have at least 1 years of specific experience in rank modelling for GEO.

GEO/AEO/SGE Experience (Mandatory): Must have 1 years of hands-on experience in

Generative Engine Optimization, Answer Engine Optimization, or Search Generative

Experience, optimizing for AI interfaces and conversational queries.

Gen-AI Execution (Mandatory): Hands-on exposure to prompt engineering, embeddings, vector search, or RAG-based systems.

Core Knowledge: Deep understanding of how up-to-date search engines and AI-driven systems rank and generate responses, including semantic search and entity-based optimization.

Ecosystem Exposure: Strong exposure to AI/LLM ecosystems such as ChatGPT, Google Gemini, or similar platforms, understanding how responses are generated and ranked.

Content Structuring: Understanding of content structuring for AI consumption (schema, context building, knowledge representation).

Pay: Up to ₹2,000,000.00 per year

Work Location: In person

📌 AI/ML Engineer (Pune)
🏢 RecruitFutures
📍 Pune