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 Infrastructure team builds the tools that build our software and scales our test infrastructure such that all developers can contribute to automated test suites. For deployments of LeapYear, Infrastructure engineers write sophisticated, parameterized installers for enterprise environments, and automate deployment into cloud environments.
We are looking for versatile problem solvers that are interested in developer productivity, automation, and cloud infrastructure.
As team lead, you will be a player-coach that writes code every day and drives critical architecture decisions. You'll also support your team with prioritization, planning, retrospectives, and mentoring, and work closely with executives from product management, solutions architecture, and operations.
For details on the specific responsibilities and requirements of this role, please see below.
Responsibilities
- Hold primary accountability for infrastructure features, from prioritization to design to release
- Lead by example, and foster a culture of openness, customer-centricity, and accountability
- Provide continuous feedback, recognition, and challenges for your team, factoring in their long-term career arc
- Develop greenfield systems and scale existing build system, deployment methods, and cloud infrastructure
- Own the full software development lifecycle - problem definition, design, development, testing, demoing, and supporting production use of the features you own.
- Conduct and automate concurrency testing, scale testing, and testing of differentially private machine learning algorithms
- Partner with product management to define problems and identify iterative solutions
- Balance immediate business objectives against long-term architectural vision, and continue to strike this balance as your team and company grow rapidly
- Contribute to an engineering-wide culture of code quality and shared responsibility for testing
Requirements
- 7+ years of general software programming experience
- 3+ years of technical leadership, building and growing teams
- Experience at startups and growth-stage tech companies
- Excellent interpersonal and written communication skills
- Advanced knowledge of at least one infrastructure automation tool such as Terraform, Ansible, Chef, Salt, or Puppet
- Good understanding of Linux systems administration, command line tools, and various distributions of Linux (Centos, Red Hat).
- Experience with Continuous Integration/Continuous Deployment tools (CircleCI preferred)
- Experience with services provided by AWS, Azure, or GCP (AWS preferred)
Preferred
- System admin experience, preferable enterprise experience
- Experience with administering and running Hadoop and Spark clusters
- Experience with Kubernetes and Docker
- Experience with Maven, Bazel, Gradle, or other modern build systems
- Acquainted with and interested in functional programming (Haskell, OCaml, Clojure, Erlang, Scala)
- Experience testing the results of statistical analysis, preferably machine learning.
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