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Experience: 5+ yrs

Location: Bengaluru

Job Type: Full-time

We are looking for an experienced Senior AI/ML Engineer - Generative AI to lead the design, development, and deployment of enterprise-scale AI solutions. The role focuses heavily on Generative AI, Large Language Models (LLMs), multimodal AI, agentic AI, RAG, and production machine learning systems .

The ideal candidate will combine strong hands-on engineering expertise with the ability to define AI/ML roadmaps, solve complex technical problems, and guide engineering teams. You will work closely with Business, Product, Engineering, Data Science, and MLOps teams to transform business challenges into scalable, secure, and production-ready AI solutions.

Requirements Key Responsibilities

- Partner with Business, Product, Engineering, Data Science, and MLOps teams to design and deliver enterprise-scale AI solutions
- Define and drive the AI/ML roadmap for key business and technology problem areas
- Lead the design, prototyping, development, and production deployment of Generative AI and LLM-based applications
- Work with models such as GPT, Claude, LLaMA, Mistral, and other foundation and multimodal models
- Build scalable Retrieval-Augmented Generation (RAG) pipelines, embedding workflows, and retrieval architectures
- Design and implement integrations with vector databases such as FAISS, Pinecone, Weaviate, and Milvus
- Develop and optimise data pipelines supporting AI/ML applications and model workflows




- Fine-tune models using approaches such as LoRA and PEFT and establish robust evaluation methodologies
- Build AI orchestration and agentic workflows using frameworks such as LangChain and LlamaIndex
- Optimise AI systems for latency, throughput, cost, scalability, accuracy, and reliability
- Monitor model performance, drift, bias, and production behaviour and implement appropriate corrective measures
- Design scalable ML deployment pipelines using cloud-native and containerised environments
- Apply appropriate CI/CD, MLOps, observability, governance, and model lifecycle management practices
- Collaborate with engineering teams to integrate AI capabilities into production applications and platforms
- Lead technical debugging, root-cause analysis, performance optimisation, and production issue resolution
- Establish best practices for experimentation, evaluation, documentation, security, and production readiness
- Mentor and guide engineers while contributing to technical standards and AI/ML engineering practices
- Evaluate emerging AI technologies and identify opportunities for their practical application

What Makes You a Great Fit
- 5+ years of experience in AI/ML engineering, with strong hands-on experience delivering Generative AI solutions into production
- Strong programming expertise in Python, with working knowledge of SQL and, where applicable,



R
- Strong experience with NumPy, Pandas, Scikit-learn, and other data science libraries
- Hands-on expertise with deep learning frameworks such as PyTorch, TensorFlow, Keras, MXNet, or Caffe
- Strong understanding of NLP, LLMs, multimodal AI, and contemporary Generative AI architectures
- Experience with Hugging Face, Transformers, SpaCy, NLTK, Gensim, or Spark NLP
- Proven experience building, integrating, evaluating, and fine-tuning LLMs
- Strong knowledge of LangChain, LlamaIndex, RAG architectures, embeddings, and vector retrieval
- Hands-on experience with Pinecone, FAISS, Weaviate, Milvus, or similar vector databases
- Strong understanding of classical machine learning techniques, including regression, SVM, decision trees, random forests, and clustering
- Experience with cloud ML platforms such as AWS SageMaker, Google Vertex AI, or Azure Machine Learning
- Hands-on experience with Docker, Kubernetes, and cloud-native deployment environments
- Strong knowledge of ML CI/CD, model observability, and governance tools such as MLflow, Weights & Biases, and LangSmith
- Strong understanding of model evaluation, monitoring, scalability, security, cost optimisation, and production reliability
- Excellent analytical and problem-solving skills with the ability to tackle complex AI/ML challenges
- Strong technical leadership, communication, stakeholder-management, and mentoring abilities
- Bachelor's, Master's, or PhD in Computer Science, Mathematics, Statistics, Engineering, or a related disciplinefrom a recognised institution is preferred

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