Building production-grade AI systems that ship, scale, and earn trust.

• Engineering Manager AI/ML

  Twilio · Bangalore
  Jan 2026 – Present
  • Lead and mentor a 7+ member ML engineering team, driving delivery across multiple ML and GenAI initiatives.
  • Own quarterly planning, roadmap definition, and execution — aligning ML strategy with business goals.
  • Scale and expand the team through hiring, onboarding, and capability development.
  • Partner with product, security, and infra teams to ensure enterprise-grade reliability, data privacy, and regulatory compliance.

• Staff Machine Learning Engineer

  Twilio · Bangalore
  Aug 2021 – Jan 2026
  • Architected and owned end-to-end AI systems for Twilio's Fraud Guard, protecting global messaging traffic and delivering $30M+ annual revenue savings through real-time fraud prevention.
  • Built and scaled a real-time SMS classification model for the Compliance Toolkit, delivering $1M+ annual revenue.
  • Designed hybrid AI architectures combining LLM-based reasoning, NLP classifiers, and rule-based systems to optimize accuracy, latency, and cost at enterprise scale.
  • Acted as a playing coach for senior ML engineers — reviewed architecture, pair-coded complex issues, and set engineering best practices across teams.
  • Drove cloud-native MLOps adoption using AWS SageMaker, MLflow, Docker, and Kubernetes for scalable, compliant deployments.

• Research Data Scientist

  Philips · Bangalore
  Dec 2019 – Aug 2021
  • Designed and deployed deep learning pipelines for automated cardiac MRI segmentation, achieving ~90% clinical-grade accuracy and enabling scalable AI-assisted diagnostics.
  • Built end-to-end ML workflows across data ingestion, training, validation, and deployment within Philips' regulated healthcare ecosystem.
  • Led adoption of internal AI platforms to enable reusable ML components across teams, reducing time-to-production for new use cases.
  • Collaborated with global stakeholders to translate research prototypes into production-ready AI services.

• Data Scientist

  Siemens · Bangalore
  May 2018 – Dec 2019
  • Developed enterprise-scale predictive systems for supply chain forecasting (97% accuracy), supporting mission-critical business planning.
  • Built NLP-based defect classification and root-cause-analysis systems, reducing software and device defects by ~50%.
  • Implemented log analysis pipelines for predictive maintenance, improving system reliability and uptime.

• Data Analyst

  Accenture · Bangalore
  Mar 2016 – Apr 2018
  • Delivered ML-driven merchandising and assortment planning systems for global retail clients, improving profitability by ~10%.

• Conference

  Agentic Video Cloning: Automated Recreation via Scene Understanding

  Featured session at DataHack Summit 2026 (Analytics Vidhya) — building agentic pipelines that understand scenes and automatically recreate video content.

• Corporate Training

  Enterprise AI Training — Claude, Copilot & Agentic AI

  Corporate training and content creation on Claude, GitHub Copilot, Agentic AI, and GenAI workflows for enterprise engineering teams.

• Corporate Training

  MLOps & End-to-End ML Programs

  Complete MLOps and machine learning training programs delivered for enterprise clients including Fractal, GM, Dentsu, and TVS.

• Corporate Training

  Building Production-Grade AI Systems

  Hands-on training on hybrid ML + LLM architectures, MLOps, and reliability for enterprise engineering teams.

• Webinar

  Agentic AI in the Real World

  Designing stateful agent workflows with guardrails, retries, and cost control — from prototype to production.

• Guest Session

  Breaking Into AI/ML

  Career-transition sessions delivered across UpGrad, Scaler, GL Academy, and Analytics Vidhya cohorts.

• Fireside

  AI System Design for Interviews

  Walkthroughs of real architecture trade-offs — serving, latency, monitoring — expected in senior ML interviews.

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