Machine Learning Architect

Job Description 

Our client is seeking a Principal Machine Learning Architect to drive their machine learning strategy and its platform architecture. This position reports to the Director of Enterprise Data Architecture and Analytics Strategy. This position will be responsible for building Machine Learning architecture and solutions to maximize the interpretation of our data in order to provide reliable predictive models. You will join a growing multi -disciplinary team of Data Scientists, Engineers and Solution experts with deep domain knowledge who are working to develop new capabilities and workflows to solve real-world problems. 

We're looking for someone who is passionate about data and analytics, has a love for solving hard business problems, and enjoys learning about new technology.

The principal architect will help lead client in defining the strategies, roadmaps and solutions to harness the value of data and analytics. This role is critical in leading the organizational transformation in the cloud data platforms and advance analytics domains. The role will:

• Define the strategy & roadmap for analytics \ deep learning frameworks and evangelize the vision to the organization.
• Design, document and lead the implementation of software and systems to help ensure optimal implementation of the neural network models, real-time analytics with enterprise data.
• Design, develop and implement Machine Learning analytics technology stack for prescriptive & predictive analytics.
• Work in conjunction with Infrastructure, Dev Ops, Security and Engineering groups to drive the strategy to provide stable, secure and enterprise-class data-lake and real-time analytics systems.
• Design highly-available data lake architectures, utilizing IaaS and PaaS, for large scale, mission critical applications and high-performance-computing (HPC) workloads.
• Provide guidance to the organization in the form of reference architectures, guidance principles, and proof of concept and reference implementations for cloud based data platforms and advance analytics tools and technologies.
• Work closely with project architects to align the projects' architectural direction with domain roadmaps, standards and reference architectures.
• Work with cross-functional departments and delivery teams to ensure that they understand the prescribed direction. Oversee the execution of key architectural initiatives within this domain.
• Hands-on in the delivery of enterprise data-lake on AWS and the required solutions to meet enterprise analytic and business intelligence needs.
• Lead design and implementation new capabilities in support of Provide guidance to other developers in the technologies being assessed and used. Assist Management with the training and mentoring of the team members.
• Collaborate with other teams to address upstream and downstream integration dependencies via services and SLA's
• Demonstrate technical leadership and ability to contribute to establishing the overall solution direction.
• Be self-starters with the initiative and enthusiasm to learn new tools & technologies within the Hadoop eco system and AWS platform in a quick paced ever-changing environment.
• Maintain a working knowledge of client’s applications and system integration..
• Lead presenter in Architecture Review Board (ARB) Process
• Evaluate and/or lead Product Evaluation Matrix (PEM) development

Our ideal candidate will have a both a software engineer background combined with a machine learning background along with strong work ethic, great attitude and be comfortable tackling any challenge set before them.

Minimum Qualifications:

• MS degree in Computer Science or related quantitative field with 5 years of relevant experience or Ph.D degree in Computer Science or related quantitative field
• Experience in one or more of the following areas: machine learning, large-scale data mining or artificial intelligence.
• Proven ability to translate insights into business recommendations
• Experience with distributed computing frameworks Yarn, kubernetes, AWS ECS
• Experience with Docker, Orchestration
• Experience with ML frameworks - TensorFlow, Caffe2, MxNet, H20, PredictionIO, CNN, RNN, Torch, Java, Scala, Python, R, CUDA, OpenCL
• Experience developing and debugging in Java/Scala/R/Python, Knowledge of functional programming
• Experience with Spark ML/Hadoop is a plus
• Experiences with AWS infrastructure is a plus