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

The Predict team builds the machine learning that powers Alloy’s core products. We started with fraud detection - helping banks spot suspicious behavior in real-time - but we’re quickly growing into something much bigger. This team is the epicenter of Alloy’s AI and ML strategy, and this hire will help supercharge our roadmap - building out our data platform, running rapid experiments, retraining models, and helping get innovative tools into client's hands to stop fraud.

This role will be a key thought partner, working with the Predict team and cross-functional leadership to make our lofty ideas a reality.  We’re already the industry leader in fraud detection and prevention for financial institutions, and we intend to stay on the cutting edge - think industry-advancing technology like banks configuring their risk systems through conversation, AI assistants handling complex reviews, and models that spot new patterns across millions of transactions.

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

What you’ll be doing

• Maintain production ML systems including feature generation, model training, model serving, and monitoring.
• Participate in building and managing the interface between machine learning systems and the Alloy application.
• Work with data scientists to ensure our machine learning algorithms generate accurate outcomes.
• Collaborate with Product and engineering organization members to develop machine learning algorithms and drive ideation about how ML/AI can be leveraged to solve critical customer pain points.
• Develop ML models with data scientists using deep learning techniques.
• Design clean interfaces and well-tested systems.
• Participate in our on-call rotation.
• Stay up-to-date with the industry developments in machine learning and lead innovation at Alloy on architecting systems that leverage leading trends and advancements in ML/AI

We’re looking for

• Strongly proficient in at least one machine learning framework (pytorch, tensorflow).
• Experience with deep learning and transformer architectures.
• 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.
• Expert-level experience with Python.
• Able to prioritize and communicate progress.
• A minimum of 5 years of experience deploying machine learning models to production systems.
• Someone who embodies our shared Alloy values: be bold, get scrappy, collaborate, and celebrate our differences.
• Must be local to Greater New York City.
• Experience working in the financial risk space is a plus, but not required.

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 $141,000 and a midpoint base salary of $166,000. 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).

Benefit