ML Engineer - II

Weekday AI; Bengaluru; On-site; INR 2,000,000 - 3,500,000; Full time

Job summary

Weekday AI is seeking an experienced AI/ML Engineer to build production-grade ML and Generative AI systems in Bengaluru. You will own end-to-end development, from design to deployment, across LLMs, RAG, conversational AI, and personalization.

You will pair strong Python and software fundamentals with hands-on experience deploying AI systems in production, working with retrieval, LLM orchestration, and scalable backend services to deliver reliable AI-powered experiences.

Qualifications

• 3+ years of experience in ML, Applied ML, NLP, Generative AI, or AI engineering.
• Strong proficiency in Python with solid software engineering fundamentals.
• Hands-on experience building applications using LLMs, RAG, embeddings, vector search, or conversational AI.

Responsibilities

• Design, develop, and own production-grade ML/AI systems end-to-end.
• Build and integrate LLM-powered applications, including RAG and conversational AI.
• Develop retrieval systems using embeddings, vector search, semantic retrieval.
• Design LLM orchestration workflows coordinating models, tools, and retrieval.
• Develop evaluation frameworks to measure quality, latency, and cost.
• Collaborate with Product and Backend teams to deliver AI-powered features.

Skills

Python

LLMs

RAG pipelines

Vector search

LangChain

Cloud computing

Tools

Pinecone

Weaviate

Milvus

pgvector

LangChain

LangGraph

Job description

This role is for one of the Weekday's clients

₹2000000 - ₹3500000 (ie INR 20-35 LPA)

Experience: 3+ yrs

Location: Bengaluru

Job Type: Full-time

We are looking for an experienced AI/ML Engineer to build and own production-grade Machine Learning and Generative AI systems end-to-end. The role focuses on developing intelligent applications using LLMs, RAG, conversational AI, agentic workflows, personalization, recommendations, memory, and user intelligence.

The ideal candidate will combine strong Python and software engineering fundamentals with hands-on experience building, evaluating, deploying, and optimizing AI systems for real-world applications. You will work across ML, retrieval, LLM orchestration, and scalable backend systems to deliver reliable and impactful AI-powered experiences.

Key Responsibilities

• Design, develop, and ownproduction-grade ML/AI systemsacross the complete development lifecycle.
• Build and integrateLLM-powered applications, including RAG pipelines, conversational AI, and agentic workflows.
• Develop retrieval systems usingembeddings, vector search, semantic retrieval, and context enrichment.
• Build AI capabilities forpersonalization, memory, recommendations, and user intelligence.
• Design LLM orchestration workflows to coordinate models, tools, retrieval systems, and application logic.
• Develop evaluation frameworks to measureLLM quality, accuracy, relevance, reliability, latency, and cost.
• Optimize AI systems for production performance, scalability, response quality, and resource efficiency.
• Combine structured domain intelligence withML, retrieval, and LLM reasoningto deliver context-aware outputs.
• Build and maintain APIs and production services that integrate AI capabilities with backend systems.
• Design scalable ML/AI architectures suitable for high-volume production environments.
• Develop experiments, prototypes, and proof-of-concepts and transition successful solutions into production.
• Implement monitoring, evaluation, debugging, and continuous improvement processes for deployed AI systems.
• Collaborate with Product, Backend, and cross-functional engineering teams to deliver AI-powered features.
• Evaluate emergingLLMs, open-source models, retrieval techniques, agent frameworks, and AI tooling.
• Contribute to engineering standards, technical documentation, model evaluation practices, and AI system design.
• Take ownership of problems end-to-end, fromdesign and implementation through evaluation, deployment, and production support.

What Makes You a Great Fit

• 3+ years of experiencein Machine Learning, Applied ML, NLP, Generative AI, or AI engineering.
• Strong proficiency inPythonwith solid software engineering and programming fundamentals.
• Hands-on experience building applications usingLLMs, RAG, embeddings, vector search, or conversational AI.
• Proven experience deploying and supportingML/AI systems in production.
• Strong understanding of machine learning fundamentals, model evaluation, experimentation, and performance optimization.
• Experience designing and developingAI APIs, scalable services, and production-ready systems.
• Strong understanding of system design, scalability, reliability, and cloud-based application development.
• Experience evaluating and optimizing LLM applications forquality, latency, cost, and reliability.
• Strong understanding of retrieval pipelines, prompt engineering, context management, and LLM orchestration.
• Ability to independently own technical problems across the complete lifecycle:design → build → evaluate → deploy → improve.
• Experience withLangChain or LangGraphis an advantage.
• Familiarity with vector databases and technologies such asPinecone, Weaviate, Milvus, pgvector, or similaris desirable.
• Experience withHugging Face and open-source LLMsis a plus.
• Knowledge ofMLOps, LLM evaluation frameworks, recommendation systems, or multilingual/Indic NLPis an advantage.
• Strong analytical and problem-solving skills with a practical, experimentation-driven approach.
• Excellent communication and collaboration skills with the ability to work effectively across Product and Engineering teams.
• Strong ownership mindset and interest in building reliable, scalable, and user-focused AI products.