# Machine Learning Engineer - 2

> Weekday AI · Bengaluru, India · Full-time · Posted 2026-09-17

**Salary:** INR 2,000,000–3,500,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟮𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 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.

## Requirements

Key Responsibilities

-   Design, develop, and own **production-grade ML/AI systems** across the complete development lifecycle.
-   Build and integrate **LLM-powered applications**, including RAG pipelines, conversational AI, and agentic workflows.
-   Develop retrieval systems using **embeddings, vector search, semantic retrieval, and context enrichment**.
-   Build AI capabilities for **personalization, memory, recommendations, and user intelligence**.
-   Design LLM orchestration workflows to coordinate models, tools, retrieval systems, and application logic.
-   Develop evaluation frameworks to measure **LLM quality, accuracy, relevance, reliability, latency, and cost**.
-   Optimize AI systems for production performance, scalability, response quality, and resource efficiency.
-   Combine structured domain intelligence with **ML, retrieval, and LLM reasoning** to 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 emerging **LLMs, 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, from **design and implementation through evaluation, deployment, and production support**.

What Makes You a Great Fit

-   **3+ years of experience** in Machine Learning, Applied ML, NLP, Generative AI, or AI engineering.
-   Strong proficiency in **Python** with solid software engineering and programming fundamentals.
-   Hands-on experience building applications using **LLMs, RAG, embeddings, vector search, or conversational AI**.
-   Proven experience deploying and supporting **ML/AI systems in production**.
-   Strong understanding of machine learning fundamentals, model evaluation, experimentation, and performance optimization.
-   Experience designing and developing **AI 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 for **quality, 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 with **LangChain or LangGraph** is an advantage.
-   Familiarity with vector databases and technologies such as **Pinecone, Weaviate, Milvus, pgvector, or similar** is desirable.
-   Experience with **Hugging Face and open-source LLMs** is a plus.
-   Knowledge of **MLOps, LLM evaluation frameworks, recommendation systems, or multilingual/Indic NLP** is 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.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/3F740F78E1/apply)

---
Powered by [Workable](https://www.workable.com)