Q
Quantiphi
ML Engineer

Senior Machine Learning Engineer

On-siteSeniorML EngineerJust posted
Role summaryAI-generated

This role focuses on architecting LLM-powered conversational AI solutions and leading agent framework development on AWS cloud infrastructure. The senior engineer will collaborate with cross-functional teams to deliver enterprise-grade systems.

Skills required

About this role

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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