Director of Artificial Intelligence

About IDfy

IDfy is Asia’s leading TrustStack, trusted by the best, with global expertise and enterprise-grade tech, we’re solving trust challenges, making compliance easy, fraud detection smarter, and onboarding seamless.

IDfy’s three platforms- OnboardIQ, OneRisk, and Privy - come together to form one seamless solution enabling trust.

1. OnboardIQ is an onboarding platform that accelerates growth with frictionless omni-channel onboarding, while mitigating fraud and improving quality of account.
2. OneRisk is a fraud and risk management platform to mitigate financial, legal, and reputational risks and avoid losses with proactive fraud prevention. It covers individual risk, entity risk, and asset risk.
3. Privy is a privacy and data governance platform to ensure DPDPA compliance through trust and privacy governance suite and avoid monetary and reputational loss.

Our clients include HDFC Bank, Induslnd Bank, Zomato, Amazon, PhonePe, Paytm, HUL and many others. We have successfully raised $27M from Elev8 Venture Partners, KB Investments & Tenacity Ventures!

We work fully onsite on all days of the week from our office in Andheri East, Mumbai

About the Role

Join our team as an AI Lead (Director, AI), where you’ll have a direct impact on the end-to-end lifecycle of our AI-driven solutions.

You will:

• Work on cutting-edge solutions that help fight fraud across geographies and modes.
• Work across the full spectrum of our production AI platform, from data acquisition and model training / fine-tuning to deployment and maintenance / enhancement.
• Own performance tuning and optimization efforts to maintain our high-performance AI systems.
• Collaborate on R&D to evaluate and integrate cutting-edge technologies, continuously enhancing our platform with the latest advancements in AI and machine learning.
• Design and build robust solutions including APIs to expose AI capabilities, ensuring the reliability and scalability of models in production, typically Bharat scale.
• Contribute to documentation and provide technical guidance to team members on best practices.

This role emphasizes model research, building, and production deployment, but you will also engage in the full lifecycle of production AI to ensure continuous improvement and system performance. You will collaborate across the organization to solve complex multimodal problems

About You

You’re a hands-on AI engineer or data scientist with 12+ years of experience driving impactful AI initiatives in production settings. You’re passionate about solving complex problems, building systems that scale, and keeping abreast of the latest AI developments.

Must-Haves

• Proven experience framing and solving complex problems with AI models, specifically in computer vision or NLP, and GenAI and deploying these at scale.
• Hands-on experience with LLMs, with expertise in fine-tuning, retrieval-augmented generation (RAG), and model selection. You should have worked on at least two production use cases in this domain. You should know what models / approaches to choose based on the use-cases and their solutions.
• You understand that model building is only a fraction of production AI work and you know what it takes to maintain high-performance AI systems.
• 6+ years building and maintaining large-scale production AI systems, including optimization and tuning for deployment at scale.
• An insatiable curiosity and passion for state-of-the-art research, combined with the drive to apply innovative approaches to real-world problems.
• Expertise in Python and knowledge of its standard and AI related libraries such as Pytorch, OpenCV, etc
• Strong skills in monitoring and debugging production AI systems for sustained reliability and efficiency.
• Experience mentoring and guiding junior engineers, sharing your expertise to uplift team knowledge.
• Capability to interact with a variety of stakeholders including senior leadership and customers from the most demanding industries
• Some familiarity with AI Ops and associated tooling to streamline AI processes.
• Cloud experience with AWS/GCP/Azure

Good-to-Haves

• Experience with other languages
• Familiarity with Docker and Kubernetes for efficient service deployment.
• Experience with a variety of platforms, frameworks, and tools in the AI and machine learning ecosystem.
• Publications and patents in the AI domain