--- title: 'Senior Machine Learning Engineer at Possible Finance' canonical: 'https://feeny.ai/job/senior-machine-learning-engineer-possible-finance-seattle-jqpjt86je2kr' type: 'job' last_seen: '2026-10-16' --- # Senior Machine Learning Engineer at Possible Finance - **Company:** Possible Finance - **Location:** Seattle, WA - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-10-02 - **Last confirmed live:** 2026-10-16 - **Apply:** https://jobs.ashbyhq.com/possible-finance/24f5ca89-d6ba-454c-a506-66eaf46bdf95 ## Job description Since our founding, we’ve delivered over $1 billion in funding to more than 1 million customers and saved them over $500 million. At Possible, we’re building a new kind of consumer finance company, one that helps people stay out of debt rather than profit from keeping them in it. ## Team Introduction Our Data Science and Data Engineering teams build the models that power how Possible extends credit responsibly — models that assess risk, detect fraud, and personalize outcomes for the people we serve. Today, though, the infrastructure behind those models — how features get built, how models get deployed, how we know when something's silently drifting — is maintained by the same people building the models themselves, layered on top of their core work. As Possible scales, that's becoming the bottleneck. We're looking for the person who takes ownership of that infrastructure long-term, so our data teams can focus on what they do best: building models that work. ## The Role & Responsibilities You'll be Possible's first dedicated owner of ML infrastructure — a green-field mandate with real autonomy to shape how we build, deploy, and monitor machine learning models going forward. In your first year, you'll design and roll out a shared feature store, giving our data teams a safe place to experiment with new features without ever touching production, and meaningfully improving how fast our models respond in real time. You'll bring visibility to a part of our systems that's currently a black box, standing up drift monitoring so we catch model degradation before it becomes a customer-facing problem. And you'll consolidate a patchwork of deployment tooling into one clean, reliable pipeline — covering not just the models we ship, but the ones we try and learn from along the way. This is a role for someone who takes ownership seriously: you'll start as a team of one, kickstarting the processes and standards Possible's ML function will run on for years, applying the same scientific rigor to your own infrastructure decisions that our data scientists apply to their models. ## Requirements - Deep, hands-on experience building and operating machine learning infrastructure — feature stores, model serving, and monitoring systems — in a production environment - A track record of solving ambiguous, undefined problems: this role has no existing playbook at Possible, and you'll build one - Strong proficiency in Python, AWS, and Databricks, with genuine engagement with the broader MLOps tooling landscape and the judgment to evaluate and choose the right tools for the job - A demonstrated drive for results, holding yourself accountable to a high, concrete bar for your own work - Comfort working cross-functionally with data scientists and engineers, bringing them along on new tooling rather than mandating it top-down - A self-starter mindset — energized, not daunted, by being the first person in a role and building what it needs from scratch ## What We Offer This is a Hybrid position. We work in our centrally located downtown Seattle office three days a week (M, T, and Th). The compensation range for this role is $187,440 to $202,350. We also offer significant stock options, comprehensive benefits, a bonus plan, commuter benefits, and excellent office space with complimentary drinks and food. With the backing of our venture investors— Union Square Ventures, Canvas Ventures, Euclidean Capital, and Unlock Venture Partners — a dedicated following of hundreds of thousands of customers, and an extraordinary team, we are unwavering in our fight for financial fairness. As one of only a few FinTech Public Benefit Corporations, we’ve baked our dual dedication to building a profitable and socially impactful company into our charter; we only succeed when our customers do too. Give us a shout if you’d like to help us ship financial products that protect consumers from predatory lending practices and promote economic health. Possible Finance is dedicated to financial fairness and community empowerment. We welcome diverse perspectives and experiences to help us achieve our mission of unlocking economic mobility for generations to come. Learn more about us as a [Public Benefit Company](https://www.possiblefinance.com/blog/we-are-now-a-public-benefit-corporation). ## About Possible Finance ## Company Overview - **One-liner**: Possible Finance is a financial technology company offering small-dollar installment loans and credit products as a fair alternative to payday lending, designed to help underbanked consumers break the debt cycle and build credit. - **Entity Type**: Private (Series B) - **Headquarters**: Seattle, Washington, USA - **Founded**: 2017 - **Founders**: Tony Huang (CEO) and Tyler Conant (CTO) ## Core Business - **Primary industry**: Fintech – Consumer lending and credit services. - **Target customers**: B2C – primarily underbanked Americans living paycheck to paycheck, those with thin or no credit history. - **Mission / Purpose**: “End the debt cycle and unlock economic mobility” (operates as a Delaware Public Benefit Corporation). ## Products & Services - **Possible Loan**: Small-dollar installment loans (up to $500) via a mobile app. Underwrites using cash-flow and bank transaction data (no FICO check). Flexible repayment (can reschedule each payment up to 29 days), no late or insufficient funds fees. Payments are reported to credit bureaus to help build credit history. - **Possible Card**: A credit card alternative launched after a 150,000+ person waitlist, designed with customer-friendly terms and no traditional credit card tactics. ## Market Standing - **Valuation / Market Cap**: Not publicly disclosed (private company). - **Key Metric**: Revenue run rate of $125 million (2025); first annual profit recorded in 2025. Total funding: $11 million Series B (2020). - **Notable Investors / Partners**: Union Square Ventures (led Series B); Coastal Community Bank (banking partner for loans in most states). - **Growth Signals**: Served over 1.5 million customers; funded more than $1 billion in loans; returned to growth after pandemic headwinds; planning to double Seattle office footprint to accommodate up to 100 local employees; ~150 employees globally (as of early 2026). ## Competitive Advantages - No penalty fees (late fees, insufficient funds fees) – saved customers over $650 million. - Cash-flow underwriting using machine learning, enabling access for those without a FICO score. - Public Benefit Corporation structure legally commits to social impact alongside profit. - Compliance-first approach, designing products that hold up to regulatory scrutiny in a highly scrutinized industry. - Loan payments reported to credit bureaus, helping customers build credit history. ## Strategic Focus - Expand product suite and serve more customers across the U.S. - Continue scaling while maintaining profitability and mission alignment. - Deepen investment in engineering and product to improve the customer experience and drive economic mobility. ## Why Work Here - **Culture**: Mission-driven, high ownership, practical and collaborative. Emphasizes impact on real people. - **Work policy**: Hybrid in Seattle – three days per week in office (downtown near Pike Place). Remote employees fly in twice a year for “Possipalooza”. - **Benefits**: Comprehensive medical/dental/vision, flexible spending accounts, 401(k), Health Savings Account contributions, discretionary time off, paid holidays plus company-wide “Week of Possibility”, paid parental leave (including fostering/adoption), wellness allowance, $300 annual home office stipend, commuter benefits in Seattle. - **Engineering culture**: Practical interviews simulating real work; high visibility and ownership; operates with startup agility while navigating complex regulations. ## Sources 1. [Possible Finance Careers](https://www.possiblefinance.com/careers) 2. [Possible Finance Homepage](https://www.possiblefinance.com/) 3. [Built In Profile](https://builtin.com/company/possible-finance) 4. [Our Story / Leadership](https://www.possiblefinance.com/our-story) 5. [GeekWire – Profitability and Rebuild](https://www.geekwire.com/2026/possible-finance-rebounds-rebuilds-and-reaches-profitability-as-founders-reunite-for-a-new-chapter/) ## Other roles at Possible Finance - [Tier 1 Customer Success Agent (Philippines)](https://feeny.ai/job/tier-1-customer-success-agent-philippines-possible-finance-philippines-80j0e0jh3kvj) — Philippines - [Customer Support Agent, Tier 1](https://feeny.ai/job/customer-support-agent-tier-1-possible-finance-costa-rica-x23hp1dydm42) — Costa Rica - [Senior Strategic Finance Manager](https://feeny.ai/job/senior-strategic-finance-manager-possible-finance-seattle-esqpj2f7m8q3) — Seattle, WA - [Senior Data Scientist](https://feeny.ai/job/senior-data-scientist-possible-finance-seattle-4xztp940xh29) — Seattle, WA - [Product Lead, App Ecosystem](https://feeny.ai/job/product-lead-app-ecosystem-possible-finance-seattle-w6k0pjtq2f65) — Seattle, WA - [Product Marketing Lead](https://feeny.ai/job/product-marketing-lead-possible-finance-united-states-rnnn65mbentq) — United States - [Lifecycle Marketing Lead](https://feeny.ai/job/lifecycle-marketing-lead-possible-finance-united-states-xj5gx6jsjfnz) — United States - [Product Lead, Loan and Advance](https://feeny.ai/job/product-lead-loan-and-advance-possible-finance-seattle-k5085m2jgmz9) — Seattle, WA - [Senior Machine Learning Engineer](https://feeny.ai/job/senior-machine-learning-engineer-taboola-los-angeles-12czs33sgk1q) — Los Angeles, CA - [Senior Machine Learning Engineer](https://feeny.ai/job/senior-machine-learning-engineer-checkout-com-london-362vyt6j2yca) — London, United Kingdom