Architect, develop, deploy, and monitor scalable machine learning and LLM-powered conversational AI systems on AWS. Lead agent framework, tool-calling, multi-agent, RAG, MLOps, analytics, and observability development while collaborating with technical and business stakeholders.
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!
Job Role - Senior Machine Learning
Experience - 4-7 Years
Location - Mumbai/ Bangalore/ Trivandrum
We are seeking a highly skilled Senior Machine Learning Engineer specializing in conversational AI and agent systems. The ideal candidate will architect LLM-powered solutions, lead agent framework development, and collaborate with cross-functional teams to deliver enterprise-grade conversational AI systems on AWS cloud infrastructure.
Must have skills:
- Architect, develop, and deploy ML solutions at scale including traditional ML and LLM/conversational AI systems
- Lead end-to-end ML/AI lifecycle: data preparation, feature engineering, model development, validation, deployment, and monitoring
- Design production-ready agent frameworks, tool calling systems, and multi-agent coordination
- Implement MLOps best practices for deployment, monitoring, and optimization across ML and LLM systems
- Proven expertise in regression, decision trees, SVM, ensemble models, clustering, data preprocessing, feature selection, and statistical modeling
- Expert knowledge of prompt engineering, context optimization, agent reasoning patterns, RAG systems, vector databases, and semantic search
- Strong Python skills with ML libraries (scikit-learn, XGBoost, LightGBM) and agent frameworks (LangChain, CrewAI)
- Experience designing and implementing robust RESTful APIs for integrating ML models and conversational AI systems with enterprise applications and external services
- Experience with AWS Services : AWS Sagemaker, Bedrock, etc.
- Build scalable conversation analytics and AI system observability frameworks
- Collaborate with data scientists, data engineers, product managers, and stakeholders to translate business requirements into scalable ML/AI solutions
- Excellent problem-solving, communication, and stakeholder management skills
Good to Have Skills:
- Advanced AI Experience: Experience with Model Context Protocol (MCP) or similar agent communication standards
- Experience in customer support automation or contact center technologies
- Cloud AI certifications (AWS ML Specialty, Azure AI Engineer, Google Cloud ML Engineer)
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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