Senior Machine Learning Engineer

Senior Machine Learning Engineer

Requirements

• PhD with 5+ years of experience or MS with 5-8+ years of industry experience in AI/ML, developing and deploying production-level ML systems.
• Proven expertise in building AI/ML models in at least one of the following domains: Ads, relevance, ranking, recommendation systems, and search.
• Breadth and depth knowledge of statistical learning, machine learning, and deep learning.
• Experience in building distributed, low-latency, high-throughput batch and online ML services.
• Hands-on experience in deploying and maintaining ML pipelines in production, including feature engineering and model monitoring frameworks.
• Fluency in Python and proficiency with distributed frameworks (Spark, Hadoop), SQL, and cloud infrastructure.
• Experience with ML packages such as Tensorflow or PyTorch, scikit-learn, and Spark ML.
• Ability to operate efficiently in a high-paced, multi-functional, and rapidly evolving environment.

Responsibilities

• Drive end-to-end lifecycle management of AI/ML projects from concept and data acquisition to prototyping, model development, deployment, and ongoing maintenance.
• Implement and champion best practices in MLOps, including data ingestion, model training pipelines, monitoring, alerting, and QA to ensure model reliability and performance.
• Contribute significantly to model architecture decisions, leveraging state-of-the-art machine learning, deep learning, and reinforcement learning techniques.
• Develop and deploy robust feature engineering pipelines and ML services optimized for low latency and high throughput.
• Establish and utilize robust A/B testing and experimentation frameworks to evaluate and iteratively improve model performance.
• Translate research papers into high-quality, production-ready code.
• Communicate effectively, collaborate, and build long-term relationships across the organization.
• Mentor junior team members in achieving engineering excellence and be a change agent on the team.

Preferred Qualifications

• 5+ years of experience in building ML models in the ads space or recommender systems.
• Experience in building CTR/CVR prediction, ad selection, keyword bidding, and Learning to Rank models.
• Experience in building and deploying online experimentation frameworks to identify right models and features at scale.
• Experience in building ad selection frameworks using reinforcement learning or contextual bandits.
• Experience in fine tuning LLMs or building them from scratch.
• Experience in building products using Generative AI powered autonomous agents.