AI/ML Engineer

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Experience: 3+ yrs

Location: Bengaluru

We are looking for a skilled and innovative AI/ML Engineer to build and scale intelligent AI systems focused on Large Language Models (LLMs), conversational AI, long-term memory, and personalization. The role involves developing advanced retrieval systems, adapting open-source models, and building domain-specific AI capabilities that deliver context-aware, accurate, and personalized user experiences.

The ideal candidate will combine strong Python programming skills with hands-on expertise in LLM engineering, Retrieval-Augmented Generation (RAG), vector databases, model fine-tuning, and production deployment.

Requirements

Key Responsibilities

• Design and develop conversational AI systems with contextual understanding, long-term memory, and personalised response generation.
• Build and optimise RAG pipelines using embeddings, vector databases, structured data, and knowledge retrieval techniques.
• Develop memory systems for user profiling, information extraction, relevance scoring, retrieval, ranking, and context selection.
• Integrate, deploy, and fine-tune open-source LLMs for specific product and domain requirements.
• Develop specialised Small Language Models (SLMs) to support domain-specific reasoning and improve response quality.
• Create domain-specific datasets and training pipelines for fine-tuning, model adaptation, and continuous learning.
• Implement LLM orchestration, prompt engineering, classification, ranking, and lightweight machine learning workflows.
• Build evaluation frameworks to measure retrieval relevance, memory accuracy, reasoning quality, response consistency, and overall model performance.
• Optimise inference latency, compute utilisation, model reliability, and deployment costs.
• Develop and maintain model-serving APIs, automated tests, monitoring systems, and production deployment workflows.
• Investigate AI failures, analyse model outputs, and implement improvements based on measurable performance indicators.
• Collaborate with Product and Engineering teams to translate user requirements into scalable AI solutions.
• Evaluate emerging LLM technologies, retrieval architectures, and model optimisation techniques to improve system capabilities.

What Makes You a Great Fit

• 3+ years of experience in AI/ML engineering, machine learning, NLP, or production AI application development.
• Strong proficiency in Python and experience building reliable, production-grade AI systems.
• Hands-on experience with LLMs, open-source models, embeddings, vector databases, and RAG architectures.
• Understanding of LLM fine-tuning, dataset preparation, model evaluation, and inference optimisation.
• Experience developing retrieval, conversational memory, context management, or personalisation systems.
• Familiarity with LLM orchestration frameworks, prompt engineering, and multi-step AI pipelines.
• Experience deploying models through APIs and implementing testing, monitoring, and production support.
• Strong analytical and problem-solving skills, with the ability to evaluate AI improvements using measurable outcomes.
• Knowledge of LoRA/QLoRA, SLMs, knowledge graphs, Neo4j, or graph-based retrieval is an advantage.
• Experience with recommendation systems, ranking models, synthetic data generation, or automated evaluation pipelines is beneficial.
• Familiarity with GPU inference optimisation and self-hosted open-source models is desirable.
• Experience in astrology, symbolic reasoning, or specialised domain-reasoning systems is an added advantage.
• Strong ownership, communication, and collaboration skills, with the ability to drive AI initiatives from experimentation through production.