ML Engineer (Recommendation systems) | Upto 75 LPA

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗷𝗼𝗯

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

𝗦𝗮𝗹𝗮𝗿𝘆: Upto 75 LPA

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

🚀 𝗪𝗵𝗮𝘁 𝗪𝗲'𝗿𝗲 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴

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.

🚀 𝗠𝗟 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 (2+ 𝗬𝗲𝗮𝗿𝘀 𝗼𝗳 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲)

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.

🧩 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗹𝗹 𝗗𝗼

• 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

✅ 𝗬𝗼𝘂'𝗿𝗲 𝗮 𝗚𝗿𝗲𝗮𝘁 𝗙𝗶𝘁 𝗜𝗳 𝗬𝗼𝘂

• 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 collaborative 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

✨ 𝗪𝗵𝘆 𝗝𝗼𝗶𝗻 𝗨𝘀?

• 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.