Software Engineer / Machine Learning Engineer
Fintech Startup (San Jose, CA)
Full-Time, On-Site
About the Company:
We're an ambitious fintech building modern financial products powered by deep technical rigor, strong engineering fundamentals, and data‑driven automation. Our team comes from top technology and financial institutions, and we're backed by leading investors. We move quickly, sweat the details, and operate with the belief that technology can dramatically improve financial access and efficiency for millions of people.
We're hiring Machine Learning Engineers and Software Engineers who want to own complex systems end‑to‑end: architecture, modeling, infrastructure, experimentation, product flows, and everything in between. You'll drive projects from idea → implementation → iteration, working across tightly coupled engineering, product, and data teams - often times working directly with executives.
You'll be a strong fit if you enjoy solving hard problems, navigating ambiguity, and operating in an environment where speed, detail‑orientation, and technical depth matter equally.
What You'll Work On:
You'll have the opportunity to build across both ML or core software surfaces, including:
Machine Learning & Data
• Predictive and decision‑making models across risk assessment, personalization, relevance, onboarding, user lifecycle, and automation
• Data pipelines, ML infrastructure, and systems for experimentation, model deployment, monitoring, and continuous retraining
• Automated processes that reduce manual back‑office workflows and streamline operational tasks
Software Engineering & Product Systems
• Consumer‑facing flows with high reliability, low latency, and graceful degradation in poor network environments
• Core backend services, distributed systems, APIs, and platform components that enable new product expansion
• Internal tooling and infrastructure enabling teams to scale operationally and technically
• Growth, activation, and engagement systems that support product adoption and user success
Cross‑Functional
• Strategic discussions informing product direction, user experience, business logic, and technical architecture
• Deep exploration of product‑domain details-legal, operational, technical, or data‑related-where precision matters
• Culture‑building: early engineers play an outsized role in shaping standards, processes, and norms for the company
Qualifications:
• 2-6 years of full-time experience, post-graduation, in software or machine learning engineering
• Have led / heavily impacted technically complex projects with multiple moving parts and cross‑functional stakeholders
• Have experience across disparate systems: distributed systems, compilers, OS‑level components, ML pipelines, or large‑scale production systems
• Ramp up quickly in new environments, codebases, or problem domains with minimal guidance
• Enjoy ambiguity and want to help define the solution rather than simply execute it
• Value depth and craftsmanship-understanding systems at the most granular level when needed
• Thrive in collaborative, fast‑paced environments where everyone contributes to product, architecture, and strategy
• Enjoy diving into challenging problems and view them as opportunities for rapid personal growth
Have career spikes such as:
• Return offers from competitive internships
• Early or fast promotions
• Recognition for impact or exceptional performance
• Come from big tech firm or top-tier engineering orgs
• Studied and received a degree at Top 25 Computer Science or related program
Tech Stack (but not limited to)
• Python / C++
• Kubernetes
• Typescript
• PostgreSQL
• Cloud infrastructure (AWS)
Apply now if you check these boxes and join a startup that is going to revolutionize their space!
• No contractors*
