3.0 - 10.0 years

0 Lacs

haryana

On-site

As the founding ML Scientist, you will be responsible for designing and deploying the core recommendation and personalization systems that drive our matchmaking experience. Your role will involve owning the entire lifecycle - from the initial design phase to deployment - while establishing a robust foundation for a scalable, real-time ranking infrastructure. In this position, your key responsibilities will include: - Owning and developing match-making, recommendation, ranking, and personalization systems. - Working on building a real-time adaptive matchmaking engine that can learn from user interactions and various signals. - Designing ranking and recommendation algorithms to create a personalized feed for each user. - Developing user embedding systems, similarity models, and graph-based match scoring frameworks. - Exploring and integrating cold-start solutions to enhance user experience. - Collaborating with Data, Product, and Backend teams to ensure exceptional customer experiences. - Deploying models to production by utilizing fast iteration loops, model registries, and observability tooling. - Establishing and nurturing the ML engineering team and its culture. The ideal candidate for this role should: - Be a full-stack ML data scientist-engineer capable of designing, modeling, and deploying recommendation systems, with experience leading initiatives in recsys, feed ranking, or search. - Have 3-10 years of experience working on personalization, recommendations, search, or ranking at scale. - Possess prior experience in a B2C product domain such as social, ecommerce, fashion, dating, gaming, or video platforms. - Have exposure to a variety of popular recommendation and personalization techniques, including collaborative filtering, deep retrieval models, learning-to-rank, embeddings with ANN search, and LLM approaches for sparse data personalization. - Demonstrate the ability to train models and deploy them, with experience in end-to-end ML pipelines. - Understand offline and online evaluation, A/B testing, and metric alignment. - Bonus points for experience with vector search, graph-based algorithms, and LLM-based approaches. Joining our team at this stage offers the opportunity to: - Be part of a founding team where your contributions are integral to the product experience. - Influence the future of human connections in the AI era. - Benefit from significant ESOPs and wealth creation, along with competitive compensation. We look forward to welcoming a passionate and skilled ML Scientist to help shape our innovative matchmaking platform.,

Posted 1 week ago

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Founding Principal ML Engineer/ ML Scientist Gloroots

3.0 - 10.0 years

0 Lacs

haryana

On-site

As the Founding Principal ML Engineer/ML Scientist at an early-stage, US-based venture-backed technology company in Gurgaon, you will have the opportunity to play a pivotal role in creating innovative platforms for building meaningful relationships. The company's focus is on leveraging artificial intelligence to transform how people connect, foster community engagement, and deliver tailored content. Rather than developing another traditional social app, the company aims to craft a unique experience that deeply resonates with users, making them feel truly understood. Central to the platform is a dynamic, machine-learning-powered recommendation system inspired by leading music and video platforms. The company strongly believes that great data combined with good models leads to great recommendations, and good data combined with great models leads to average recommendations. Therefore, the company is committed to investing in data infrastructure from the very beginning. As the founding ML engineer, your responsibilities will include designing and deploying core recommendation and personalization systems that power the matchmaking experience. You will be responsible for the full lifecycle of these systems, from design to deployment, while also laying the foundation for scalable, real-time ranking infrastructure. Key Responsibilities: - Own and develop match-making, recommendation, ranking, and personalization systems. - Create a novel, real-time adaptive matchmaking engine that learns from user interactions and other signals. - Design ranking and recommendation algorithms to curate each user's feed. - Build user embedding systems, similarity models, and graph-based match scoring frameworks. - Explore and integrate cold-start solutions. - Collaborate with Data, Product, and Backend teams to deliver exceptional customer experiences. - Deploy models to production using fast iteration loops, model registries, and observability tooling. - Build and nurture the ML engineering team and culture. The ideal candidate for this role is a full-stack ML data scientist-engineer with 3-10 years of experience in personalization, recommendations, search, or ranking at scale. Previous experience in a B2C product environment, such as social, ecommerce, fashion, dating, gaming, or video platforms, is preferred. Exposure to a variety of recommendation and personalization techniques, including collaborative filtering, deep retrieval models, learning-to-rank, embeddings with ANN search, and LLM approaches for sparse data personalization, is desirable. Experience with end-to-end ML pipelines, offline and online evaluation, A/B testing, and metric alignment is also crucial. Knowledge of vector search, graph-based algorithms, and LLM-based approaches is a plus. In return, you will have the opportunity to join a founding team where your work is essential to the product experience. You will help shape the future of how humans connect in the AI era and receive significant ESOPs, wealth creation, competitive cash compensation, and a chance to work in a cutting-edge environment.,

Posted 1 week ago

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