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Senior Machine Learning Engineer at fast-growing lending startup at fast-growing lending startup at Petal (New York, NY)

The Risk Engineering team Join a team of bright, motivated, and collaborative engineers using design patterns, machine learning, and a great attitude to wrangle complex, ever-changing business rules engines under control. These mission-critical systems need to evaluate accurately at all times and hold up to compliance and legal scrutiny. These systems also leverage Petal’s secret sauce to qualify applicants for credit (even without a credit report!) and help keep the business safe from fraud. To get this job done, we value open communication, diversity of thought, and a keen eye for detail. We also value cute puppies, obscure rock bands, disaster films, the word “prime”, and penguins.  Sound interesting? Then keep reading and hit that apply button!

Key responsibilities

    • Help us expand access to fair and honest credit to the underbanked by delivering and supporting scalable production-grade decisioning services, including productionizing machine learning models and backtesting new experiments
    • Lead technical design and system architecture for services that determine who we lend to
    • Mentor junior engineers and uphold our high engineering standards for maintainable, well tested, and performant software
    • Work across the broader engineering organization to improve best practices and influence system design
    • Plan complex projects, influence product design and make business vs technology trade-offs during all phases of the project lifecycle
    • Collaborate with various Petal teams (e.g., product, analytics, risk, compliance) and third-party technology vendors (e.g., credit bureaus, data aggregators)
    • Develop and use a nuanced understanding of our risk philosophy and policy to implement complex decisioning logic safely

Characteristics of a successful candidate

    • 5+ years of experience - or equivalent proficiency - in designing, developing, testing, shipping, and scaling service-oriented/distributed applications or systems.
    • Strong self-management, sense of ownership, and organization. Petal’s open and collaborative environment enables proactive and organized employees to really shine.
    • Collaborative, empathetic, listens with intent. Communication of complex, ever-changing business and technology concepts is hard. Creating a shared understanding and path forward via an open discussion is commonplace at Petal. 
    • Passionate about systems design and robust software. Our underwriting decisioning systems change often as we work and experiment to bring credit to as many people as we can. We are passionate about software architecture and fault tolerant production systems. 
    • Detail-oriented; a strong focus on testing frameworks. Petal’s underwriting systems are complex and mission-critical. We rely on strong testing frameworks and a focus on the details of requirements to deliver features correctly. 
    • Weighs trade-offs and focuses on value delivery. A fast-paced startup demands making trade-offs that balance the near term and long term value add of solutions. At Petal, we design robust systems, but try not to let the perfect be the enemy of the good.
    • Displays positivity, kindness, and humility. Our open and collaborative culture is what makes Petal a great place to work. We need more diverse people who embody our core values to make it even greater.

Nice-to-haves

    • Preferred but not required: Demonstrated expertise in Python
    • Preferred but not required: Experience with machine learning models (and running them in production)
    • Preferred but not required: Financial sector experience, notably within credit and fraud risk decisioning
    • Preferred but not required: Experience working in highly regulated industries