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Description
Role: Founding Principal ML Engineer/ ML Scientist Function: Applied AI Engineer (Vision/GenAI) Location: Gurgaon Type: Full-time Compensation: 50-80+ LPA + ESOPs About the Company: An early-stage, US-based venture-backed technology company focused on creating innovative platforms for building meaningful relationships. They aim to transform how people connect by harnessing artificial intelligence, fostering community engagement, and delivering tailored content. Rather than developing another conventional social app, they’re crafting a unique experience that resonates deeply with users, making them feel truly understood. Central to our platform is a dynamic, machine-learning-powered recommendation system, drawing inspiration from the personalised discovery engines of leading music and video platforms. With strong financial backing from top-tier venture capital firms in India and the United States, they are well-positioned to advance our mission with innovation and impact. Company Philosophy: They believe: Great data + Good models = Great recommendations Good data + Great models = Average recommendations That’s why they’re investing in data infrastructure from our inception and foundation. Position Overview: As the founding ML engineer, you’ll design and deploy the core recommendation and personalisation systems that power our matchmaking experience. You’ll own the full lifecycle - from design to deployment - while laying the foundation for scalable, real-time ranking infrastructure. Role & Responsibilities: Own and develop match-making, recommendation, ranking and personalisation systems. Work on creating a novel, real-time adaptive matchmaking engine that learns from user interactions and other signals Design ranking and recommendation algorithms that make each user's feed feel curated for them Build user embedding systems, similarity models, and graph-based match scoring frameworks Explore and integrate cold-start solutions Partner with Data + Product + Backend teams to deliver great customer experiences Deploy models to production using fast iteration loops, model registries, and observability tooling Build the ML engineering team and culture Ideal Profile: You are a full-stack ML data scientist-engineer who can design, model, and deploy recommendation systems and ideally have led initiatives in recsys, feed ranking, or search 3–10 years of experience working on personalisation, recommendations, search, or ranking at scale Prior experience in a B2C product – social, ecommerce, fashion, dating, gaming, or video platforms Exposure to a wide range of popular recommendation and personalisation techniques, including collaborative filtering, deep retrieval models (e.g., two-tower), learning-to-rank, embeddings with ANN search, and LLM approaches for sparse data personalisation. Can train models AND ship them – experience with end-to-end ML pipelines Understands offline and online evaluation, A/B testing, and metric alignment Experience with vector search, graph-based algorithms and LLM-based approaches is a big plus What we offer: Join a founding team where your work is core to the product experience Shape the future of how humans connect in the AI era Significant ESOPs and wealth creation + competitive cash compensation Show more Show less
