Senior Applied Scientist - AI/ML

The Role:

We are seeking an experienced machine learning generalist who can build and deploy machine learning models in the ultra low latent search ads ecosystem. As one of the founding members of our new ML organization, you will play a crucial role in optimizing our ad serving platform and will have a clear career progression path and numerous opportunities for both personal and professional growth in an intellectually stimulating and dynamic work environment.

Responsibilities:

• Manage the entire process of ML projects and solutions, from concept development to data acquisition, prototyping, model development, and implementation in production.
• Create and implement procedures and tools to track and evaluate the performance and accuracy of models and data.
• Provide thought leadership, subject matter expertise and serve as trusted advisor in machine learning, deep learning, and other state of the art AI techniques.
• Experience delivering high quality software at scale in a low latency environment.
• Translate research papers into high-quality, production-ready code.
• Take responsibility and ownership of features and drive key architectural decisions.
• 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.

Basic Qualifications:

• A PhD with 2-3 years of experience or an MS with 3-5 years of experience in a quantitative field with experience building production systems or have equivalent experience working with large ML projects in industry.
• Proven expertise in building ML models in at least one of the following domains: NLP, 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.
• Knowledge of how to deploy and maintain ML services in a production environment.
• Experience in designing and deploying feature engineering pipelines in production.
• Deep expertise in model monitoring and ML ops including containers and orchestration.
• Fluency in one of the programming languages, preferably Python or Java.
• Experience with Spark, Hadoop or other distributed frameworks, SQL, and cloud services.
• 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.

Preferred Qualifications:

• 5+ years of experience in building ML models in the ads space or search relevance.
• 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.

*Compensation Range: $170,000 - $220,000 

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