The company is looking to enhance its ultra-low-latency ad-serving platform and consumer-facing search solutions through the development and optimization of advanced machine learning models.
Requirements
- 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.
- Knowledge of how to deploy and maintain ML services in a production environment.
- 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.
Responsibilities
- Manage the entire process of AI/ML projects and solutions, from concept development to data acquisition, prototyping, model development, and deploying the model in production.
- Create and implement procedures and tools to track and evaluate the performance and accuracy of models and data.
- Translate research papers into high-quality, production-ready code.
- Take responsibility and ownership of features and drive key model architectural decisions.
- Design and deploy feature engineering pipelines in production.
- Deploy and maintain ML services in a production environment.
- Monitor and operate ML services including containers and orchestration.
Other
- A PhD with 5 years of experience or an MS with 5-8 years of experience in a quantitative field with experience building production systems or have equivalent experience working with large ML projects in industry.
- 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.
- Ability to operate efficiently in a high-paced, multi-functional, and rapidly evolving environment.
- Comprehensive healthcare, wellness programs, paid time off, commuter benefits, and 401k matching.
- Summer Fridays, catered lunches, a fully stocked kitchen, ZogSports teams, happy hours and corporate retreats to encourage a strong work/life balance.
