Gofynd

Head of AI/ML

EngineeringMumbai, IndiaFULL TIMEPosted 6/25/2026

Role Overview

Lead the AI/ML strategy and execution for the retail business, building advanced models that improve customer personalization, operational efficiency, and revenue growth. This role will shape and scale recommendation engines, demand forecasting, and other intelligent systems that turn data into measurable business impact across the organization.

Responsibilities

  • Define and own the AI/ML roadmap aligned to retail business priorities and growth objectives.
  • Lead the design, development, and deployment of recommendation engines, demand forecasting models, and other predictive solutions.
  • Build and mentor a high-performing AI/ML team, fostering technical excellence, innovation, and delivery discipline.
  • Partner with product, engineering, data, and business stakeholders to identify high-impact use cases and translate them into scalable solutions.
  • Ensure models are robust, interpretable, monitored, and continuously improved for performance, reliability, and business value.
  • Drive the application of advanced AI techniques including deep learning, NLP, and computer vision where relevant to retail use cases.
  • Establish best practices for ML lifecycle management, experimentation, data quality, and model governance.
  • Collaborate with leadership to assess technology investments, prioritize initiatives, and communicate progress and outcomes clearly.

Qualifications

Required

  • Bachelor's or Master's degree in Computer Science, Engineering, or equivalent experience
  • 10+ years of experience in AI/ML, data science, or related engineering leadership roles
  • Proven experience building and scaling recommendation engines and forecasting models
  • Strong expertise in advanced machine learning, deep learning, and statistical modeling
  • Experience applying AI/ML solutions in retail or consumer-facing businesses

Preferred

  • Experience leading AI/ML teams and setting technical strategy
  • Hands-on experience with MLOps, model monitoring, and production deployment
  • Exposure to cloud-based data platforms and large-scale distributed systems
  • Experience with experimentation frameworks and A/B testing
  • Prior work on customer personalization, revenue optimization, or supply chain use cases

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