Machine Learning Startups Seattle

While you don’t need to have experience in every technology we use, as a startup, we do expect you to be comfortable contributing everywhere on the front-end and to a lesser extent on the back-end stacks. Expert level experience with Javascript using Angular, React or Node frameworks. Experience in any of the following languages: Go, Python or Java. Experience with cloud configuration and deployment technologies. Experience developing applications in AWS. Enthusiasm for actively mentoring and giving feedback, as well as receiving feedback from others. Rigor in automated testing, continuous integration, DevOps and other engineering best practices. Agile enough to jump into a broad range of projects. BS and/or MS in computer science or a related field. 7+ years experience in software engineering.

As an engineer on the Data Science Infrastructure team, you will design and build infrastructure and tooling to make it fast, easy, and cost effective to perform machine learning experimentation and data analysis. Ensuring data and batch processing pipeline availability, stability, and access at production scale is critical to our mission.

Own the systems and tools that enable the engineering organization to build, test, deploy and run production systems with the highest availability and performance. Own the self-service tools for engineers to provision and scale infrastructure on public cloud platforms. Own services frameworks for scalable development of microservices (service discovery, traffic routing, etc.). Champion SRE principles and best practices within the engineering organization to improve safety, reliability, and security of our services. Work with engineers and leaders across the organization to improve developer productivity. Build out the team to achieve the above goals.

The core of this role is delivery of projects at all scales. This means you are not only able to develop and drive cross organization strategic initiatives, but can also roll up your sleeves, dig in and deliver cross team features and projects. As a TPM, you will anticipate bottlenecks, provide escalation management, anticipate and make tradeoffs, and balance the business needs versus technical constraints. You have the ability to take large, complex projects and break them down into manageable pieces, develop functional specifications and then deliver them in a successful and timely manner.

As an engineer on the Applications team, you will be designing and building systems that enables Sift’s customers to act and respond to machine learning insights in real time. Running MapReduce over hundreds of Hadoop nodes, designing HBase tables for terabytes of data, and building real-time, high-scale, fault-tolerant distributed systems are all everyday parts of the job. Additionally, you will always be thinking about our customers and ensuring that the software we write is focused on solving their real-world problems.