AI/ML Engineer

Relanto; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Relanto is seeking a passionate AI/ML Engineer to develop scalable ML models and end-to-end AI pipelines for predictive analytics, classification, regression, and forecasting. You will design GenAI solutions and RAG architectures to enable enterprise use cases, and build autonomous AI agents with planning and memory management.

The role requires strong Python skills, experience with LangChain and vector databases, and a solid understanding of MLOps, AI evaluation, and responsible AI practices.

Qualifications

• Bachelor's degree in CS/IT/AI or related field.
• Minimum 1 year experience in data science and ML, preferably NLP/GenAI/LLMs.
• Experience with LangChain, LlamaIndex, vector DBs like Pinecone/Elasticsearch.
• Proficiency in Python and ML libraries.
• Experience with cloud platforms (AWS/Azure/GCP) for deploying ML solutions.
• Experience with AI model evaluation, prompt optimization, and Responsible AI practices.
• Knowledge of API integration and microservices architecture.
• Design GenAI apps integrating OpenAI GPT, BERT or open-source LLMs.
• Deep understanding of RAG architectures and their implementation.
• Knowledge of SQL generation using LLMs is a plus.
• Strong problem-solving and analytical skills; solid English communication.

Responsibilities

• Develop and deploy scalable ML models for predictive analytics, classification, regression, and forecasting.
• Build end-to-end AI pipelines from data preprocessing to monitoring.
• Develop and fine-tune GenAI and LLMs for enterprise use cases.
• Design RAG architectures using vector databases and embeddings.
• Build autonomous AI agents with planning, memory management, and tool usage.
• Establish best practices for generative models in business contexts.
• Collaborate with leadership to identify AI opportunities and promote strategy.
• Deliver production-grade AI solutions following modern software practices.

Skills

Python programming

NLP / GenAI / LLMs

MLOps / LLMOps

LangChain / LlamaIndex

Vector databases

Cloud platforms (AWS/Azure/GCP)

API integration / microservices

AI model evaluation / prompt tuning

Responsible AI practices

Agile development

English communication

Education

Bachelor's degree in computer science / IT / AI or relevant discipline

Job description

Responsibilities

• Develop,Design, develop, and deploy scalable Machine Learning models for predictive analytics, classification, regression, recommendation, clustering, and forecasting problems.
• Build end-to-end AI pipelines covering data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring.
• Develop and fine-tune Large Language Models (LLMs) for enterprise use cases.
• Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and embedding models.
• Build autonomous AI agents capable of planning, reasoning, memory management, and tool usage.
• Contribute to the establishment of best practices for efficient utilization of generative models in business and automation contexts.
• Work with leadership and stakeholders to identify AI opportunities and promote strategy.
• Be able to deliver solutions following modern software development practices.

Required Skills

• Bachelor's degree in computer science, IT, AI or relevant discipline
• Must have minimum of 1 year of work experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps/LLMOps, Optimization techniques, and AI solutions.
• Specific experience in GenAI and Conversational AI – LLMs, frameworks like Lang chain, Llama Index etc, Vector DBs like Pinecone, Elasticsearch, etc.
• Solid proficiency in Python programming and related AI/ML libraries.
• Experience with cloud platforms (AWS, Azure, or GCP) for deploying and scaling AI/ML solutions.
• Experience with AI model evaluation, prompt optimization, and implementation of Responsible AI practice
• Knowledge of API integration, microservices architecture, and production-grade AI application deployment.
• Design GenAI application, integrating advanced models like OpenAI’s GPT, BERT or Open Source LLMs.
• Deep understanding of the RAG architecture and its implementation.
• Knowledge in SQL generation using LLM is preferred.
• Ability to write high-quality, maintainable code and work collaboratively.
• Knowledge of Agile software development lifecycle, including experience of applying change control procedures and disciplines required.
• Problem solving with strong analytical skills with the ability to analyse complex requirements and define technical / functional advanced solutions.
• Excellent communication skills in both verbal and written English