Position: Senior Backed Software Engineer
Company: Sift
Category: Java
Experience required: 5y
English level: upper

Required skills
- 5+ years experience building distributed backend systems using Java, Scala, C#, C++, or other object-oriented languages.
- 3+ years experience working with large datasets using Apache Spark, MapReduce, or similar technologies.
- 3+ years experience with cloud infrastructure (e.g. GCP, AWS, Azure).
- Strong software engineering fundamentals, including data structures, algorithms, and distributed systems, and strong debugging, testing, and problem-solving skills.
- Strong communication & collaboration skills, and a belief that team output is more important than individual output.
- You are a self-starter, with a quick learning curve.

As a plus
- Experience with stream processing systems such as Apache Flink, Apache Beam, Dataflow, or similar technologies.
- Experience with HBase, BigTable, Kafka, ZooKeeper.
- Familiarity with practical challenges in ML systems, such as feature extraction and definition, data validation, training, monitoring, and management of features and models.

We offer
- Competitive total compensation package
- Medical, dental and vision coverage
- Wellness reimbursement
- Education reimbursement
- Flexible time off

Sift is an equal opportunity employer. We make better decisions as a business when we can harness diversity in our experience, data, and background. Sift is working toward building a team that represents the worldwide customers that we serve, inclusive of people from all walks of life who can bring their full selves to work every day.

Responsibilities

What we’re looking for:

As a senior software engineer on the team that builds Sift’s Digital Trust and Safety Product, you will work closely with product managers, data scientists and other software engineers to deliver various product features, which are at the intersection of machine learning and distributed systems. Specifically, you will:
- Design and build highly scalable, distributed microservices that can handle hundreds of millions of events per day.
- Design and build offline experimentation systems used to simultaneously evaluate tens of thousands of models.
- Scale machine learning pipelines used to produce thousands of models derived from terabytes of data.

About the team

At Sift, we enhance trust and safety in the digital world with our AI driven technology platform. Our products deliver payment protection, ensure content integrity, and protect account abuse and takeover for businesses around the world. We believe that machine learning is the way to empower internet-scale businesses to prevent fraud and improve trust.

We are a group of software engineers and data scientists working on products to enhance trust and safety of the internet. By providing a clear, accurate assessment of risk at multiple points of the end-user journey, we enable businesses to eliminate losses from fraud, and create adaptive, frictionless experiences for end-users. You will have the opportunity to collaborate with strong engineers, product managers and designers to build highly available and real-time systems to detect and prevent fraud for our customers.

Project description

Sift is the leading innovator in Digital Trust & Safety. Hundreds of disruptive, forward-thinking companies like Airbnb, Zillow, and Twitter 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.

Our team bridge the gap between our platform providing machine learning at scale and our customers’ needs. We give our customers a seamless way to gain insights, make decisions, and navigate the ever-changing world of fraud-fighting. We provide customer-facing automated workflow tools running on highly-available services architecture. We’re also responsible for providing third-party extensibility points, giving our customers simple ways to use our product within their current workstreams. Together we provide the platform that makes high-volume streams of data understandable, actionable, and usable.