About the team:
Every day, thousands of websites and apps rely on Sift’s cloud-based machine learning to understand which users and actions they can trust. With this knowledge companies can prevent fraud, grow revenue, and build better user experiences based on trust.
The Data Science Infrastructure team owns the tools that empower the development of new machine learning models and data intelligence at Sift. Experimentation is the lifeblood of machine learning. Our tools simplify the processes for experimentation in the face of greater complexity and scale. They also make it easier to find and analyze the data needed to make decisions.
What we’re looking for:
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.
What you’ll do:
- Design and build tooling to enable data scientists and ML engineers to quickly iterate on experiments
- Motivate, teach, listen and empathize with a variety of engineering and analytical roles
- Lead architecture discussions to meet the requirements of machine learning teams at the scale of thousands of models and hundreds of terabytes of data
- Implement scalable, high-throughput, fault-tolerant, extensible, and easily maintainable batch processing workflows
- Champion and deliver cross-company data engineering initiatives
What would make you a strong fit:
- Designed and built scalable, fault-tolerant batch services for production data
- Experience iterating on large, complex ETL data pipelines that stretch the limits of available tools and services
- Strong software engineering fundamentals
- Strong communication & collaboration skills, and a belief that team output is more important than individual output
- Experience with big data and related systems
- Experience building backend systems using Java / Python
- Familiar with distributed backend data stores (HBase, Cassandra, etc.) and CAP theorem
- Knowledge of container technologies / AWS
- Experience working with large datasets using Spark / MapReduce
A little about us:
Sift is the leading innovator in Digital Trust & Safety. Hundreds of disruptive, forward-thinking companies like Airbnb, Patreon, Zoosk, and ChowNow trust Sift to deliver outstanding customer experience while preventing fraud and abuse.
The Sift engine powers Digital Trust & Safety by helping companies stop fraud before it happens. But it’s not just another anti-fraud platform: Sift enables businesses to tailor experiences to each customer according to the risk they pose. That means fraudsters experience friction, but honest users do not. By drawing on insights from our global network of customers, Sift allows businesses to scale, win, and thrive in the digital era.
Benefits and Perks:
- Competitive total compensation package
- 401k plan
- Medical, dental and vision coverage
- Wellness reimbursement
- Education reimbursement
- Flexible time off
- Catered meals
Sift is an equal opportunity employer. Our core value of “Be Tough On Ideas And Excellent To Each Other” is built on a foundation of diversity and inclusion; we work together to ensure the best ideas win. We hire people with different perspectives, educational backgrounds, and life experiences, because we know this makes us stronger, healthier, and more innovative. Our commitment to belonging enables us to bring our full selves to work so we can contribute our talents in meaningful ways and “Win As One Team."