Founding ML Scientist Meant To Be Inc
Meant To Be Inc
Office Location
Full Time
Experience: 3 - 3 years required
Pay:
Salary Information not included
Type: Full Time
Location: Haryana
Skills: Machine Learning, Matchmaking, data science, recommendation systems, Personalisation Systems, Ranking Algorithms, ML engineering, Model deployment, Model Registries, Observability tooling, Fullstack ML Data ScientistEngineer
About Meant To Be Inc
Job Description
As the founding ML Scientist, youll design and deploy the core recommendation and personalisation systems that power our matchmaking experience. Youll own the full lifecycle - from design to deployment - while laying the foundation for scalable, real-time ranking infrastructure. What You'll Do: 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 310 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 Why Join Us Now: 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 c,