Applied Research Scientist – Machine Learning

Overview

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 environmen

Company:

ADP

Qualifications:

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
Industry
Computer Software Financial Services Human Resources
Employment Type
Full-time

Job Functions
Other

Educational level:

Ph. D.

Tagged as: Clustering, Industry, Machine Learning, Pattern Recognition, Ph. D., Recommendation System, United States