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This role is for one of our client companies — a VC-backed Social networking startup that has raised $10.5M USD in funding.

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Apply once and, if selected, get access to up to 20 remote and onsite interview opportunities.

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CodeRound AI matches the top 5% tech talent with the fastest-growing, VC-funded AI startups across Silicon Valley and India.

Top-tier product startups across the US, UK, EU, UAE, and India have hired top engineers through CodeRound.

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We’re looking for a hands-on Machine Learning Engineer to build and scale the core real-time recommendation, ranking, and personalization engines powering a next-generation social platform. If you want to own the entire ML lifecycle from modeling to production, let’s connect.

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- Design, build, and deploy matchmaking, recommendation, ranking, and personalisation systems
- Develop a real-time adaptive recommendation engine that learns from user interactions and other behavioural signals
- Build ranking algorithms that deliver highly personalised and curated user experiences
- Develop user embeddings, similarity models, and graph-based match-scoring frameworks
- Research and implement cold-start solutions for users and recommendations with limited data
- Experiment with collaborative filtering, deep retrieval, learning-to-rank, embeddings,



ANN search, and LLM-based approaches
- Own the full lifecycle of recommendation models, from problem definition and modelling to deployment and monitoring
- Establish and improve offline and online evaluation frameworks, A/B tests, and recommendation metrics

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- 2–7 years of experience working on recommendation systems, personalisation, search, feed ranking, or related ML problems at scale
- Strong hands-on experience building recommendation, ranking, or personalisation models
- Experience with a B2C product, ideally in social, ecommerce, fashion, dating, gaming, video, or other consumer platforms
- Understanding of recommendation techniques such as cooperative filtering, learning-to-rank, embeddings, similarity models, and retrieval systems
- Experience with end-to-end ML pipelines, including model development, experimentation, and/or production deployment
- Strong understanding of offline and online evaluation, A/B testing, and metric alignment

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- Own the entire machine learning pipeline from inception to production deployment.
- Build core AI features for millions of users on our platform.
- Fast-track your career in a well-funded, rapidly growing startup environment.
- Collaborate daily with top-tier engineers driven to shape social connection.

📌 ML Engineer (Upto 75 LPA) (India)
🏢 CodeRound AI
📍 India