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Experience: 2+ yrs

Location: Bengaluru

Job Type: Full-time

We are looking for a technically strong Generative AI / Machine Learning Engineer to design, develop, and deploy intelligent applications powered by Large Language Models (LLMs), AI agents, and machine learning systems. The ideal candidate will have hands-on experience in Python, agentic AI, Retrieval-Augmented Generation (RAG), LLM frameworks, and production-ready AI engineering .

This role is suited for an engineer who enjoys solving complex problems, experimenting with emerging AI technologies, and transforming research concepts into scalable, reliable, and high-performing applications.

Requirements Key Responsibilities 2. Retrieval-Augmented Generation (RAG) 3. LLM Optimisation and Fine-Tuning 4. Machine Learning and Deep Learning 5. Deployment and MLOps

- Generative AI and Agent Development
- Design and develop LLM-powered applications and autonomous or semi-autonomous AI agents
- Build agentic workflows using LangChain, LangGraph, LlamaIndex, or similar frameworks
- Implement function calling, tool integration, and multi-step reasoning workflows using approaches such as ReAct
- Develop end-to-end AI systems that can plan, execute tasks, and interact with external tools and APIs
- Design and implement scalable RAG pipelines for document-based knowledge retrieval and contextual response generation
- Work with vector databases such as Pinecone, FAISS, and Milvus
- Optimise document chunking, embedding generation, indexing, and retrieval strategies
- Evaluate retrieval quality, improve response relevance, and implement techniques to minimise LLM hallucinations
- Experiment with prompt engineering, context management, and response-quality optimisation
- Fine-tune models using LoRA, PEFT, and related parameter-effective techniques where appropriate
- Apply quantisation techniques, including 8-bit and 4-bit quantisation, to improve inference efficiency




- Develop an understanding of model alignment approaches, including RLHF
- Apply machine learning techniques to structured and unstructured datasets
- Demonstrate an understanding of neural networks, backpropagation, regularisation, and model evaluation
- Work with algorithms such as XGBoost and Random Forest for tabular prediction tasks
- Understand foundational architectures such as RNNs, LSTMs, and CNNs where relevant
- Train and optimise models using GPU/TPU-based environments when required
- Build production-ready AI and ML pipelines with appropriate testing, deployment, and monitoring
- Track model performance and identify data drift, concept drift, and quality degradation
- Collaborate with engineering teams to integrate AI capabilities into applications and services
- Improve reliability, scalability, latency, and resource utilisation across deployed AI systems

What Makes You a Great Fit
- 2-5 years of experience in AI/ML engineering, Generative AI, or a related software engineering field
- Strong programming skills in Python and hands-on experience with LLM frameworks
- Proven experience building RAG pipelines, AI agents, and tool-using systems
- Good understanding of vector databases, embeddings, retrieval optimisation, and prompt engineering
- Knowledge of practical techniques for evaluating LLM outputs and mitigating hallucinations
- Solid fundamentals in machine learning, deep learning, model training, and evaluation metrics such as precision and recall
- Familiarity with class imbalance, model validation, and performance optimisation
- Experience with LoRA/PEFT, quantisation, GPU-based training, or LLM inference optimisation is an advantage
- Exposure to MLOps, model deployment, monitoring, and real-time AI applications is desirable
- Strong analytical, debugging, and problem-solving skills
- Ability to translate complex requirements into practical AI solutions and collaborate effectively with cross-functional teams
- A proactive learning mindset and genuine interest in emerging AI technologies and production-grade AI systems

📌 Senior AI Engineer (Bengaluru)
🏢 Weekday AI (YC W21)
📍 Bengaluru