Lead Machine Learning Engineer

What you'll do

• Drive end-to-end lifecycle management of AI/ML projects from concept to maintenance
• Implement and champion best practices in MLOps including data collection, model training pipelines, deployments, monitoring, alerting, and QA
• Contribute to model architecture decisions using state-of-the-art ML, deep learning, and reinforcement learning
• Develop and deploy feature engineering pipelines and ML services optimized for low latency and high throughput
• Establish and utilize A/B testing and experimentation frameworks to improve model performance
• Translate research papers into production-ready code
• Communicate and collaborate across the organization
• Mentor junior team members and act as a change agent

Requirements

• PhD with 5+ years or MS with 5-8+ years of industry experience in AI/ML
• 2+ years building AI/ML models in ads, relevance, ranking, recommendation systems, or search
• 3+ years building distributed, low-latency, high-throughput batch and online ML services
• 3+ years deploying and maintaining ML pipelines in production including feature engineering and model monitoring
• 2+ years experience in Python and distributed frameworks (Spark, Hadoop), SQL, and cloud infrastructure
• 2+ years experience with ML packages such as TensorFlow, PyTorch, scikit-learn, Spark ML
• Ability to operate efficiently in a high-paced, multi-functional, rapidly evolving environment
• Preferred: 5+ years building ML models for ads, search, recommender systems including CTR/CVR prediction, ad selection, keyword bidding, Learning to Rank
• Preferred: 2+ years building and deploying online experimentation frameworks
• Preferred: 2+ years building ad selection frameworks using reinforcement learning or contextual bandits
• Preferred: Experience fine tuning LLMs
• Preferred: 1+ years building products using Generative AI powered autonomous agents

Tech stack

Benefits