Socure · Dec 1st 2020
Founded in 2012, Socure is the leader in high-assurance digital identity verification technology. Named to Forbes’ 2019 AI 50 list as one of America’s most promising AI companies, and a recent winner of API World’s Best Data API, Socure’s technology applies artificial intelligence and machine learning techniques with trusted online/offline data intelligence from email, address, phone, IP, social media and the broader Internet to verify identities in real-time. Customers include three of the top five U.S. banks, seven of the top 10 U.S. card issuers, as well as the majority of leading digital banks, lenders and insurers across the U.S. We are funded by some of the world's best investors and entrepreneurs including Scale Venture Partners, Commerce Ventures, Work-Bench, Santander InnoVentures and Two Sigma Ventures
The only way we can further our mission of becoming the single, trusted source of identity verification and eliminating identity fraud is by building the best team on the planet. This is where you come in!
Socure is looking for a Senior Data Engineer to join our US engineering team and support our Machine Learning Platform team.
In our mission to become the single, trusted source of identity verification and eliminate identity fraud from the internet, machine learning is at the core of the solutions we build. It’s how we innovate and how we offer the most accurate Identity Verification on the market. With the company growing very fast and our customer needs even faster, the only way for us to succeed in our mission is to significantly scale how we experiment and collaborate during the building of ML solutions.
We are in the early stages of building a ML Platform to accelerate and automate all our ML operations and unlock the creation of our future products, and we’d love you to join us and help lead the way.
What You'll Be Doing:
You will develop and refine core components of the ML Platform
You will build and maintain production-level python libraries. Additionally, you’ll drive best practices in version control and continuous integration / delivery
Leverage open-source tools and cloud computing technologies
Own and drive initiatives from conception to completion and production monitoring
Collaborate with data scientists, engineers, product teams and other key stakeholders
You will work in a fast-paced cross-functional environment
What You’ll Bring:
You have strong previous experience in data engineering, software engineering, MLOps, data science or research
You’re familiar with best practices in the data engineering and MLOps community and have strong opinions but are flexible and open minded and are able and willing to consider other points of view
You have experience working with relational and NoSQL databases. Data warehousing experience, particularly with Redshift, is a plus
You like to think at scale and design, develop and operate terabyte-scale data pipelines and services that meet goals of low latency, high availability, resiliency, security and quality
You develop with an empathy for people and how they use your work, particularly with translating requests from data scientists and other stakeholders into requirements
You have a strong python programming background and pride yourself on writing clean, testable code
You have experience with containerization (Docker) and container-orchestration systems such as Kubernetes; experience with data workflow managers such as Drake, Luigi, or Airflow is a bonus
You have experience with cloud ecosystems. Experience with AWS is a plus
Bonus points: you have experience or familiarity with MLOps tools such as MLFlow and Kubeflow, and have experience building and deploying ML models
Perks & Benefits:
Competitive base salary
Equity - every employee is a stakeholder in our upside
Medical, dental and vision benefits for employees and their dependents
Parental leave and fertility support
Flexible PTO
401K with company match
Stipend to supply your home office
Annual professional development stipend
A Message on COVID-19: