Senior ML Engineer

As a Senior ML Engineer, you will lead the design and deployment of cutting‑edge recommendation and personalization solutions that drive user engagement across our digital ecosystems.

Responsibilities

• You will collaborate closely with data scientists, product managers, and engineering teams to build high‑throughput, low‑latency recommendation engines that adapt in real time to user behavior and contextual signals.
• By leveraging graph-based match‑scoring, sophisticated ranking models, and innovative cold‑start strategies, you will enhance the relevance of content and product suggestions for millions of users worldwide.
• Your work will directly influence key metrics such as click‑through rate, conversion rate, and user retention, while ensuring scalability, robustness, and maintainability of the underlying machine learning infrastructure.
• Design, develop, and production‑grade real‑time recommendation pipelines that process millions of events per day.
• Engineer graph‑based match‑scoring algorithms to uncover latent user‑item relationships and improve match quality.
• Build and fine‑tune ranking models using learning‑to‑rank, gradient‑boosted trees, or deep neural network approaches.
• Develop cold‑start solutions for new users and items using hybrid collaborative filtering, content embeddings, and transfer learning.
• Perform feature engineering at scale, ensuring feature freshness, consistency, and low latency latency requirements.
• Collaborate with data engineering teams to optimize data ingestion, storage, and retrieval for recommendation workloads.
• Conduct rigorous A/B testing, statistical analysis, and interpret model outputs to drive data‑driven decisions.
• Mentor junior ML engineers, sharing best practices, code review, and debugging techniques.
• Stay abreast of industry research, publish findings, and iterate on emerging techniques such as reinforcement learning or multi‑armed bandit frameworks.
• Ensure robust monitoring, logging, and alerting for model drift, latency, and error rates across all services.

Requirements

• 4+ years of hands‑on experience building large‑scale recommendation systems in a production environment.
• Deep expertise in personalization, ranking, and real‑time recommender architectures.
• Strong background in graph theory, graph neural networks, and bipartite graph matching for recommendation tasks.
• Proven track record of addressing cold‑start challenges with innovative techniques and measurable impact.
• Proficiency in Python, SQL, Spark/Databricks, and a major cloud platform (AWS, GCP, Azure).
• Solid experience with ML frameworks such as TensorFlow, PyTorch, LightGBM, and XGBoost.
• Demonstrated ability to translate metrics and business objectives into actionable ML solutions.
• Excellent communication skills, capable of presenting complex technical concepts to non‑technical stakeholders.
• A collaborative mindset, comfortable working in cross‑functional teams in a fast‑paced, iterative environment.
• Passion for staying current with academic research and industry trends, and willingness to experiment with new ideas.

Pay

Salary: INR 2,500,000–8,500,000

• 𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟮𝟱𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟴𝟱𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟮𝟱-𝟴𝟱 𝗟𝗣𝗔)
• Experience: 4+ yrs

Senior ML Engineer

Weekday AI · Delhi, India · Full-time · Posted 2026-11-14

Description

• 𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀
• Location: NCR, Delhi, India

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[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/FDC7DC8D36/apply)