Machine Learning Engineer

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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 their 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 their 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've been investing in data infrastructure from the inception and foundation.

Position Overview:

As an ML Engineer, you'll design and deploy the core recommendation and personalization systems that power their matchmaking experience. You'll engineer the full lifecycle - from design, R&D, to deployment - while laying the foundation for scalable, real-time ranking infrastructure.

What You'll Do

● develop match-making, recommendation, ranking and personalization systems.

● Work on a 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 feed feel curated for them

● Build user embedding systems, similarity models, and graph-based match scoring frameworks

● Deploy models to production using fast iteration loops, model registries, and observability tooling

Ideal Profile

● You are a ML engineer who can design, model, and deploy recommendation systems and ideally have worked on recommendation systems, feed ranking, or search

● 3-6 years of experience working on ML Engineering or Data Science.

● Prior experience working in personalization, recommendations, search, or ranking at scale

● Exposure to a variety of popular recommendation and personalization techniques, including collaborative filtering, deep retrieval models (e.g., two-tower), learning-to-rank, embeddings with ANN search, and LLM approaches for sparse data personalization.

● Can train models AND ship them - experience with end-to-end ML pipelines

● Experience with vector search, graph-based algorithms and LLM based approaches 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