Job Description

LeapYear's secure machine learning platform is deployed by some of the largest enterprises in the world across finance, healthcare, and technology.
Our technology ensures differential privacy, a widely recognized standard of data privacy that enables all data - including sensitive information - to be utilized for analytics, while providing mathematically proven privacy protection.
The LeapYear system is composed of a core set of components that allow private machine learning on data sets that can scale to petabytes. The core includes private algorithms for relational operations, statistical methods and machine learning. A data scientist accesses private data using a Python API. The system includes services for authentication, access control, logging, auditing  and support for integration of data from a variety of data sources including SQL/NoSQL Databases, HDFS and S3. Queries are processed using Spark to support to enable fast, distributed processing of massive datasets. Administration is provided  via a web-based GUI or an API
As one of LeapYear's field engineers, you will be responsible for the deployment of LeapYear's machine learning platform into complex customer environments. LeapYear works with some of the largest enterprises across healthcare, financial services, and technology, and enables full utilization of previously inaccessible data. We need technical field engineers who are comfortable designing and deploying complex systems and thinking quickly on their feet to resolve customer issues.
For details on the specific responsibilities and requirements of this role, please see below.

Responsibilities

Provide customers with a solution design for the LeapYear platform that can meet their business goals.
Own reference architectures and network topology diagrams across customers
Own the process for deploying and upgrading the LeapYear platform in customer environments
Scope, conduct, and document experimental deployments for our evolving machine learning platform running on Spark
Help our customers resolve critical issues related to software evaluation and go-live production deployment
Collaborate with the Engineering team building the LeapYear platform via structured feedback and special initiative projects.
Contribute to continuous improvement, scalability, and automation of our deployment practices
Build our internal knowledge base, as well as tools and infrastructure for LeapYear's team of customer-facing data scientists and solutions architects

Requirements

Customer-facing experience deploying and integrating enterprise software
Experience with deploying customer solutions in containerized and non containerized environments
Broad knowledge of enterprise architecture, networking, databases. Interest in data science and machine learning
Hands-on experience deploying and maintaining systems in AWS/GCP/Azure (AWS preferred)
Experience working with Hadoop and/or Spark
Strong Linux/Unix administration skills
Experience analyzing and integrating with customer's existing systems (e.g. authentication, monitoring, logging)
Prior experience troubleshooting production issues, staying calm under pressure
Effective written and verbal communication skills. Comfortable interfacing with customer personnel from system admins to technical IT leaders

A Few of the Perks

Culture of teaching and learning
Competitive compensation package of salary and equity
Catered lunch every day
Company outings
Build your ideal work station
Generous health insurance plan
Relocation support and visa sponsorship