Machine Learning Engineer
Hang- Full Time
- Senior (5 to 8 years)
Candidates should possess 8+ years of experience building production systems with at least 4 years focused on machine learning at scale, holding a Bachelor’s degree in Computer Science, ML, or a related field, with a Master’s degree or PhD preferred. They must have a proven track record of deploying and maintaining ML systems serving billions of requests, expertise in modern ML frameworks such as TensorFlow, PyTorch, and JAX, and strong foundations in distributed systems and cloud platforms, particularly GCP. Furthermore, they should be able to combine LLM with classical ML models to solve complex problems beyond RAG, and demonstrate proficiency in both real-time inference and batch processing at scale.
The Staff Machine Learning Engineer will architect and implement production ML systems handling billions of daily requests with sub-second latency requirements, design sophisticated optimization algorithms for bidding strategies, campaign performance, and audience targeting, build both real-time inference pipelines and large-scale batch processing systems, create evaluation frameworks balancing performance, cost, user experience, and advertiser ROIs, pioneer natural AI interactions enhancing user workflows, develop collaborative AI systems augmenting human decision-making, design ML features requiring zero training, provide technical leadership through mentorship and knowledge sharing, guide junior ML engineers, collaborate with executive stakeholders to align ML strategy with business objectives, and partner with a full-stack team to deliver end-to-end solutions.
Programmatic advertising for Connected TV campaigns
MadHive focuses on programmatic advertising in the Connected TV (CTV) space, providing tools for clients to plan, execute, and measure their TV ad campaigns. Its platform includes features for performance prediction, custom reporting, and audience targeting across Over-The-Top (OTT) markets in the U.S. What sets MadHive apart is its decisioning engine and data mapping capabilities, which allow for precise targeting in 210 domestic Designated Market Areas (DMAs). The company's goal is to improve the efficiency and effectiveness of TV advertising through advanced technology.