Senior Machine Learning Engineer, Predict

Alloy is where you belong! 

Alloy solves the identity risk problem for companies that offer financial products by enabling them to outpace fraud and confidently serve more people around the world. Banks and Fintechs turn to Alloy to take control of fraud, credit, and compliance risk, and grow with the clearest picture of their customers.  

Through our values: Be Bold, Get Scrappy, Collaborate, and Celebrate Our Differences, we are creating a workplace where you can grow, thrive, and belong. See how we’ve been continuously recognized and named one of Inc.Magazine’s Best Workplaces, Forbes America’s Best Startup Employers, Best Fintech to Work for by American Banker, year after year.  

Check out our investors and read more about us here.  

About the team

Alloy operates in a hybrid-work environment. We look to foster collaboration and community by having our local employees onsite twice a week. 

We’re seeking an experienced member to join a lean/focused team to drive our real-time machine-learning fraud capabilities. The Predict team is focused on building machine learning into Alloy’s product to improve our clients' decision-making and help them manage their risk. Because the team's work introduces foundational capabilities for risk management, the team is expected to work with teams across Alloy.

What you’ll be doing

The Predict Team is developing capabilities to:

• Architect scalable, fault-tolerant batch and real-time systems to power our machine learning systems.
• Work across the teams at Alloy to keep up to speed with relevant data that signals can be extracted from, and formulate approaches to get those into our systems.
• Build and manage the interface between the machine learning system and the Alloy application.
• Building machine learning systems that are optimized for low latency and high availability.
• Ensure that our machine learning algorithms generate accurate outcomes.
• Collaborate with Product & Engineering organization members to develop machine learning algorithms.
• Designing clean interfaces and well-tested systems.
• Participate in hardening our feature generation systems, both real-time and batch. The technologies we use for feature generation include Flink, Kinesis, and Sagemaker.
• Participate in our on-call rotation.
• Stay up-to-date with the industry developments in machine learning.

We’re looking for

• Experience deploying machine learning models to external facing applications.  
• Experience deploying to production, including best SDLC practices, CI/CD and IaC.
• Experience with streaming technologies such as Kafka, Kinesis, Flink, or Spark.
• A minimum of 5 years experience writing production-level code as a software/data engineer, with at least 2+ years of professional experience building product features and leveraging machine learning to external-facing users.
• Someone who embodies our shared Alloy values: be bold, get scrappy, collaborate, and celebrate our differences.
• Someone who thrives in crafting solutions that serve immediate needs, and keeps in mind how these solutions can enable the broader engineering organization’s goals.
• Strongly proficient in at least one machine learning framework (pytorch, tensorflow).
• A portfolio of successful projects demonstrating a commitment to product excellence
• Deep technical expertise with a background in software development:
• Proficient in writing Python, terraform, and javascript.  Technical dexterity and the ability to develop with high proficiency are more important.
• Ability to give thorough code reviews and help engineers solve bugs
• Experience with AWS infrastructure
• Experience with highly scalable and highly available application architectures
• Able to prioritize and communicate progress in a timely manner.
• We like to set ambitious goals without sacrificing on the quality of the things that get shipped.
• Able to work across multiple teams across Alloy.
• Must be local to Greater New York City
• Extra credit:
• Experience working with Typescript
• Some experience with Java/Scala.

At Alloy, we strive to attract & retain talent by providing compensation that is competitive with other organizations of our size & stage. We are committed to ensuring each candidate has what they need to be successful in their role with a balanced range of compensation, equity, perks & benefits. We actively share our compensation philosophy with employees, with the goal of fostering open and honest dialogue. Finally, we work to administer our philosophy and drive consistency in order to promote equity and monitor the fairness of each outcome.

This position has a minimum base salary of $199,000 and a midpoint base salary of $234,000. The base pay may vary depending on job-related knowledge, skills, and experience. In addition to a competitive base salary, this position is also eligible for equity awards in the form of stock options (ISOs).

Benefits and Perks 

• Unlimited PTO and flexible work policy
• Medical, dental, vision plans with HSA (monthly employer contribution) and FSA options
• 401k with 100% match up to 4% of annual employee compensation with immediate eligibility and vesting 
• Eligible new parents receive 16 weeks of paid parental leave
• Home office stipend for new employees
• Health & wellness monthly stipend
• $1,000 learning & development annual stipend
• Well-being benefits include access to OneMedical and Headspace

We're a lean team, so your impact will be felt immediately. If this all sounds like a good fit for you, why not join us?

How to Apply

Apply right here. You've found the application!

Alloy is proud to be an equal opportunity workplace and employer. We’re committed to equal opportunity regardless of race, color, ancestry, religion, gender, gender identity, parental or pregnancy status, national origin, sexual orientation, age, citizenship, marital status, disability, or veteran status. We are committed to an inclusive interview experience and provide reasonable accommodations to applicants with visible and invisible disabilities. We encourage applicants to share needed accommodations with their recruiter.