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 system includes private algorithms for relational operations, statistical methods and machine learning. A data scientist accesses private data using a Python API. Administration is provided via a web-based GUI or an API.
LeapYear's platform team builds the services that allow our product to integrate with complex enterprise environments and operate effectively on our customers’ most sensitive data.
The platform 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 data sets. The services are primarily written in Haskell, with Python, Scala, and Java used as additional supporting languages.
We are looking for platform engineers that have a track record of developing enterprise-ready features for technical end users, including enterprise integrations, rigorous security, flexible deployment, and support for diverse data sources.
Recent technical challenges we've been working on
Developing a new query engine in Scala to support Snowflake as well as Spark compute backends.
Refactor distributed differential privacy algorithms to achieve terabyte and petabyte scale.
Using Haskell to implement enterprise-ready subsystems for authentication, permissioning, job management, and logging.
Extending the platform to support automated daily data updates.
For details on the specific responsibilities and requirements of this role, please see below.
Responsibilities
- Develop greenfield systems and scale existing services to support internet-scale deployments.
- Own the full software development lifecycle - problem definition, design, development, testing, demoing, and supporting production use of the features you own.
- Partner with product management to define problems and identify iterative solutions
- Balance immediate business objectives against long-term architectural vision
- Contribute to an engineering-wide culture of code quality and shared responsibility for testing
Requirements
- 7+ years of professional experience writing production code
- Track record of delivering high-quality product features on schedule
- Experience working with data-at-scale compute platforms
Preferred
- Experience developing for on-premise enterprise deployments
- Acquainted with and interested in functional programming (Haskell, OCaml, Clojure, Erlang, Scala)
- Prior experience developing production-level Spark applications or machine learning platforms
- Experience with ODBC/JDBC databases, AWS, CircleCI
- Lifelong learners and mentors
A Few of the Perks
- Culture of teaching and learning
- Competitive compensation package of salary and equity: $150,000 – $250,000, depending on skills and experience
- Matching 401k plan
- Generous health insurance plan
- Disability, accident, and life insurance
- Relocation support
- Company outings
- Build your ideal work station
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