AI Engineer

Responsibilities

• Design, build, and maintain high availability, multi-tenant training, and inference system for many different content types, such as images and other sensor data
• Work closely with data scientists, micro-service developers, and data engineers in our Applied Research and Product Organizations to ensure efficient transfer of scalable solutions
• Implement seamless tracking of the lineages of data sets, transformations, feature sets, and hyper-parameters used during ML model training and inference
• Enable online learning and automated, continuous delivery of ML models
• Implement and deploy automated auditing systems to identify bias and other potential degradations of model performance
• Adapt and implement AI models to support real-world use-cases and satisfy production requirements as needed

Basic Qualifications

• MS or Ph.D. in quantitative fields (CS, Statistics, Math, or Engineering)
• 7+ years of work experience as MLE, Data Scientist, or related job function
• Strong understanding of ML fundamentals and scaling methodologies (e.g., ability to implement an ML algorithm mathematical formulations in an efficient manner w.r.t. scalability, optimization and so on; understanding of ML loss functions, evaluation/validation methods, statistical testing and so on)
• Strong communication skills both written and verbally
• You are excited to learn, explore new problem areas, and apply your creativity to some of the most challenging and rewarding problems
• Familiarity with all aspects of the model development lifecycle
• Experience working with cloud products (AWS, GCP, or Azure)
• Proficiency in Python, and experience in C++
• Prior experience with MLFlow
• Knowledge of at least one build tooling system
• Track record of writing robust, readable, well documented, well tested, high-performance code.
• Experience with containerization, automated eval/testing, CI/CD, MLOps, and cloud services is a plus