Madhive is the leading tech company engineered for modern TV advertising. Advertisers seamlessly customize and automate the OTT buying process into an operating system with our self-service platform. Powered by our industry-leading bidder and device graph that processes 260 billion available ad opportunities per day, we deliver precise, brand-safe, audience connections efficiently at scale.
We are seeking a highly skilled and experienced Staff Machine Learning Engineer. In this role, you will lead and contribute to developing and implementing machine learning models and algorithms to drive innovation and improve our products and services.
To give you an idea of what we’re working on, we deal with a massive scale of data and currently undertake millions of requests a second. To use it, we need the ability to move it around, aggregate, maintain, distill, and discover usable insights that power our platform. We’re at the edge of technology, and our engineers push the limits of what’s possible with the best technologies. As a Staff Machine Learning Engineer, you’ll work on various projects based on the intersection of your affinities, abilities, and development goals.

• Lead the design, development, and optimization of machine learning models and algorithms for various facets of our platform, including sophisticated bidding strategies, search & data retrieval functionalities, and user experience enhancements.
• Work closely with data engineers and data scientists to gather and preprocess data, ensuring its quality and relevance for model training.
• Identify and create meaningful features from raw data to enhance model performance and accuracy.
• Develop robust evaluation metrics and methodologies to assess the performance of machine learning models and fine-tune them as needed.
• Collaborate with DevOps and software engineering teams to deploy machine learning models into production environments, ensuring scalability and reliability.
• Stay up-to-date with the latest advancements in machine learning and AI research, and apply innovative techniques to solve complex problems.
• Provide guidance and mentorship to junior machine learning engineers, helping them grow their skills and capabilities.
• Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and domain experts, to understand business requirements and deliver effective solutions.
• Maintain clear and organized documentation of machine learning models, algorithms, and processes for knowledge sharing and future reference.
• Participate in an on-call rotation schedule to provide timely response and support for engineering-related issues outside of regular business hours, ensuring the continuous operation of critical systems and infrastructure.