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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
- Solid 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

📌 Machine Learning Engineer - 2 (Bengaluru)
🏢 Weekday AI (YC W21)
📍 Bengaluru