Quantiphi
Website:
quantiphi.com
Job details:
While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Role: Machine Learning Engineer
Experience Level: 2+ Years
Work location: Mumbai, Bangalore & Trivandrum
Notice Period: 0- 15 days
Role & Responsibilities
- Develop and optimize "Agentic" workflows for complex business processes like Buyer Automation and Hour Meter extraction.
- Implement advanced RAG (Retrieval-Augmented Generation) and tool-calling capabilities to enable agents to interact with external APIs and databases.
- Experience with high-reasoning models like Claude 3.5 Sonnet, with open-weight alternatives (Llama 3.1) for cost and performance optimization.
- Develop robust benchmarking and evaluation pipelines using frameworks like LangSmith or RAGAS to track extraction accuracy.
- Fine-tune and prompt-engineer models to handle specific industrial data formats and unstructured documents.
- Collaborate with Data Engineers to build seamless data pipelines that feed into agentic reasoning modules.
- Optimize model latency and token consumption to ensure scalable and cost-effective deployments.
Skills Expectation
- Expertise in LLM Orchestration patterns (ReAct, Chain-of-Thought, multi-agent collaboration).
- Deep experience with Azure AI services, including AI Search, AI Foundry, and Azure OpenAI.
- Strong background in software architecture, including microservices and event-driven patterns (Azure Service Bus).
- Proficiency in Python, advanced prompt engineering and techniques ML frameworks (PyTorch, TensorFlow).
- Experience with AI Governance, compliance, and risk mitigation strategies.
- Expert-level knowledge of LangChain, LangGraph, or Haystack.
- Hands-on experience with vector databases and semantic search optimization.
- Proven experience in deploying and monitoring LLMs in a production environment.
- Implement tool-calling functions for agents using Playwright or Selenium to navigate and extract data from vendor portals lacking native APIs.
- Develop the logic for the Streamlit-based review application to present agent outputs to business users.
- Familiarity with containerization (Docker, Kubernetes) for ML model serving.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Click on Apply to know more.