ML Engineer

About Inscribe

Inscribe is a Series B company backed by $38M in venture capital from seasoned Silicon Valley investors like Threshold Ventures, Crosslink Capital, Uncork Capital, and Y Combinator, along with angel investors including Box co-founder Dylan Smith and Intercom co-founder Des Traynor. 

We’re on a mission to create a fair and efficient financial services ecosystem — one that grants more access to “thin file” customers (who have traditionally been left behind) while keeping fraudsters out. Companies that use Inscribe are able to grow faster, reduce fraud, and serve more customers with a better experience.  

It’s a lofty goal, but one that our team of kind, funny, and wildly talented people from across the globe are committed to. We put people first by fostering an environment that is inclusive of diverse backgrounds, encouraging a sustainable work-life balance, and ensuring our team members have the resources and support to grow. Plus, our work anniversary gifts can’t be beat: poems, portraits, and (yes, it’s true) custom crossword puzzles created in your honor.

What about our company values? We’re glad you asked: 

• We’re builders: We create things that move society forward and let our work speak for itself.

• We’re here to win: We know where we’re going, and nothing will stop us from getting there.

• We’re kind: We’re human. We crave to understand others and to be understood.

• We have fun: We believe joy unlocks curiosity, creativity, and connection.

We work with some of the fastest-growing fintechs in the world, such as TripActions, Ramp, Bluevine, Shift, and more. While we’re a remote-first company, we have HQs in San Francisco and Dublin, Ireland.

The Opportunity

As a ML Engineer at Inscribe you’ll apply your technical knowledge to solve real customer problems. You’ll join the Automation team working on our core document automation logic. You’ll work closely with product managers, designers, machine learning experts and other engineers. You will be responsible for creating new methods of automating document workflows, think type and institution classification and parsing of financial documents. You’ll also tune those models to make fintech on-boarding and underwriting efficient. You will have the opportunity to see your solutions go from initial idea to production in a matter of days.

Responsibilities

• Build new document automation systems

• Collaborate with the team during the research and development process of new systems

• Write well-designed, documented, and testable code

• Monitor and evolve existing production models

• Evaluate and act on customer feedback

• Identify and execute on improvements to the teams MLOps capability

• Consider security implications in the design and implementation of your software

About You

• Have 3+ years professional experience as a Machine Learning Engineer or in a similar role

• Have experience with machine learning, computer vision, or statistics

• Are naturally curious and willing to dig deeply into a problem to find a solution

• Are thoughtful about code quality and software architecture

• Are familiar with Python or similar programming languages

• Have a degree in Computer Science, Mathematics, Engineering or another relevant field

Nice to Have

• Experience with AWS SageMaker

• Knowledge of the Fintech industry especially risk teams

• Experience building ML Models for document analysis

We’re a remote-first organization with an annual company-wide offsite and regular co-working opportunities in SF and Dublin.

Benefits

At Inscribe, we are building a company and culture where everyone can produce their best work. Here are a few of our awesome benefits:

• Competitive salary and meaningful equity

• Comprehensive healthcare

• Flexible working hours and unlimited vacation policy

• 10 company holidays and 1 floating holiday of your choice

• Complete work from home setup

• Wellness and learning stipend

Inscribe provides equity employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type with regards to  race, color, religion or religious belief, ethnic or national origin, nationality, sex, genetics,  gender, gender identity, sexual orientation, disability, age, military or veteran status, disability status, or any other basis protected by applicable local, state, or federal laws or prohibited by company policy.