22 hours ago
Mumbai, India or Bengaluru, IndiaMid Level / Senior
Responsibilities
- Architect, develop, and deploy traditional ML and LLM-powered conversational AI solutions at scale.
- Lead the end-to-end ML and AI lifecycle, including data preparation, feature engineering, modeling, validation, deployment, monitoring, and optimization.
- Design production-ready agent frameworks, tool-calling systems, multi-agent coordination, prompt strategies, RAG systems, and semantic search solutions.
- Implement MLOps practices and build conversation analytics and AI system observability frameworks.
- Develop RESTful APIs that integrate ML models and conversational AI systems with enterprise applications and external services.
- Collaborate with data scientists, data engineers, product managers, and stakeholders to translate business requirements into scalable solutions.
Requirements
- 4–7 years of experience.
- Strong Python skills and expertise with scikit-learn, XGBoost, LightGBM, LangChain, and CrewAI.
- Expertise in regression, decision trees, SVM, ensemble models, clustering, data preprocessing, feature selection, and statistical modeling.
- Experience designing and deploying ML and LLM systems, agent frameworks, RAG systems, vector databases, semantic search, and MLOps workflows.
- Experience with AWS services, including AWS SageMaker and Amazon Bedrock.
- Strong problem-solving, communication, and stakeholder management skills.
- Experience with Model Context Protocol or similar agent communication standards is preferred.
- Experience with customer support automation or contact center technologies is preferred.
- Cloud AI certifications such as AWS ML Specialty, Azure AI Engineer, or Google Cloud ML Engineer are preferred.
Categories
About Quantiphi
Quantiphi is an AI-first digital engineering and consulting firm that designs and implements machine learning, data, and cloud solutions for large enterprises across industries. Its teams build production systems—such as generative AI applications, computer vision, and predictive analytics—primarily on Google Cloud and other hyperscalers, delivered as professional services and managed solutions. Founded in 2013 and headquartered in Marlborough, Massachusetts, the company is privately held and a Google Cloud partner.