Responsibilities

• Design, build, and train highly scalable custom models and evaluate model performance
• Adapt standard machine learning methods to apply to our use cases and to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
• Suggest, collect, and synthesize requirements and contribute to creating an effective feature roadmap
• Help the team deploy production ready models to customers, to learn from customer feedback and make frequent model improvements
• Contribute to the overall architecture and implementation of our ML infrastructure, data pipelines, inference engine(s), APIs, and products
• Collaborate with our engineering and product teams to understand their machine learning related needs and to provide guidance and support where necessary
• Participate in functional, technical, and code reviews
• Work in an Agile environment

Minimum Qualifications

• Currently has or is in the process of obtaining a PhD degree or completing a postdoctoral assignment in the field of Machine Learning or similar
• Must be available to start employment on or after July 1, 2019
• Able to obtain work authorization in the US beginning in 2019
• Research and/or work experience in machine learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval or computer vision
• Experience in systems software or algorithms
• Knowledge in Python, including experience with ML related packages such as NumPy and pandas
• Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as ICML, NIPS, KDD or similar
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or used contributions in open source repositories (e.g. GitHub)

Preferred Qualifications

• Experience in applying machine learning for a global-scale enterprise or consumer application
• Demonstrated knowledge and ability working with AWS, Google Cloud, or other cloud-based solutions to train models, set up data pipelines, and set up inference engines
• Experience in microservices, Kubernetes, Docker, or other containerizers
• Working knowledge of Node.js, JavaScript, and related technologies and frameworks
• Knowledge of Continuous Integration & Delivery methodologies
• Excellent problem-solving skills especially debugging of complex software systems
• Excellent written and verbal communication skills
• A passion for applying latest technologies into the development of innovative features and products
• A collaborative attitude and demonstrated team-working ability
• Self-motivated with a strong passion for learning