Job Title

Role Overview As an SDE II – Machine Learning, you will be a core contributor in designing, building, and scaling ML-driven systems that power our real-time ad platforms. You'll be responsible for full-stack ML development—from data engineering and model development to scalable deployment—working closely with product, data science, and engineering teams.What You'll Do · Build and deploy machine learning models for ranking, bid optimization, and click-through rate prediction. · Design scalable and fault-tolerant data pipelines and services that serve real-time and batch ML workloads. · Work with large volumes of structured and unstructured data to extract meaningful patterns. · Collaborate with data scientists to convert prototypes into production-ready systems. · Build systems to intelligently target ads and content by combining contextual and behavioral signals. · Use LLM learning to improve ad relevance, page understanding, and user targeting. · Continuously experiment and optimize models based on user feedback and system performance.Some Interesting Challenges You'll Solve · Predicting CTRs and revenue across millions of unique URLs and topics in real-time. · Solving cold-start problems with sparse data using explore-exploit frameworks. · Matching contextual and behavioral data for enhanced user targeting. · Designing real-time bidding systems that optimize for revenue and win rate. · Leveraging LLMs/NLP to extract intent and context from web content.Tech Stack You'll Work With · Languages: Python, Java, Node.js · ML/Big Data: Apache Spark, Hadoop, TensorFlow/PyTorch, Kafka · Databases: SQL, MongoDB, Redis, Elasticsearch · Cloud: GCP or similarWhat We're Looking For · 3–6 years of hands-on experience in software development and ML engineering. · Strong programming and debugging skills, preferably in Python and Java. · Experience building and deploying ML models in production environments. · Solid understanding of ML algorithms (e.g., decision trees, gradient boosting, deep learning). · Hands-on experience with large-scale data processing tools (e.g., Spark, Hadoop). · Ability to design low-latency, high-throughput systems. · Strong problem-solving and analytical skills.Bonus Points · Prior experience with ad tech, recommender systems, or real-time bidding. · Publications or contributions to ML research or open-source projects. · Experience with NLP, LLMs, or Information Retrieval. · Exposure to auction theory or game-theoretic modeling.#IIT#NIT#IIIT#IISc#Jadavpur university#VIT#BITS Pilani