PayJoy Logo

PayJoy

Machine Learning Director

Posted 25 Days Ago
Be an Early Applicant
Hybrid
San Francisco, CA, USA
300K-321K Annually
Senior level
Hybrid
San Francisco, CA, USA
300K-321K Annually
Senior level
Lead PayJoy’s ML platform organization and manage Staff and Senior ML and software engineers. Define the long-term roadmap for ML infrastructure, feature stores, model serving, ETL, internal APIs, deployment, monitoring, and MLOps. Partner with Risk, Fraud, Engineering, Product, and Data Science stakeholders to translate business goals into scalable technical solutions. Mentor engineering leaders, ensure production reliability and compliance, identify operational bottlenecks, and guide adoption of technologies such as LLMs and graph databases.
The summary above was generated by AI
About PayJoy
 
PayJoy, a Public Benefit Corporation, is a mission-first credit provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success.  Our patented technology for secured credit provides an on-ramp for new customers to enter the credit system.  Through PayJoy’s point-of-sale financing and card offerings, customers gain access to a modern quality of life.  PayJoy’s credit also allows our customers to seize opportunities as micro-entrepreneurs, and acts as insurance for tough times. Through our cutting-edge machine learning, data science, and anti-fraud AI, we have served over 18 million customers as of 2025 while achieving solid profitability for sustainable growth.
 
This role

As PayJoy’s ML Platform Director, you will lead a team of very talented Machine Learning Engineers and Software Engineers that are responsible for the end-to-end ML ecosystem at PayJoy. This includes ML infrastructure: feature stores (online and offline), model serving, ETL/feature architecture and the infrastructure that helps us serve our customers like our internal offers API.


You will bridge the gap between business strategy (Risk, Fraud, Product) and technical execution, ensuring that our ML infrastructure is scalable, secure and world-class. You are a leader who enables senior-level engineers to solve the company’s most complex problems, fostering an environment where innovation meets production-grade reliability.


You will be part of a data science team on a mission to improve access to credit and technology in emerging markets with the opportunity of creating a big and real positive impact to our millions of users across the countries we operate in.


Key Responsibilities
  • Define the technical roadmap for our ML platform, modeling and internal APIs infrastructure, moving beyond individual projects to oversee the long-term sustainability of our "assembly line" approach to data products and ML model + offers serving.

  • Mentor and manage a team of Staff and Senior-level ML Engineers. Foster a culture of technical excellence, focusing on system design, scalability and code quality.

  • Act as the primary liaison between Data Science/ML Engineering and business stakeholders like Risk, Fraud, Engineering and Product. Translate complex business goals into actionable technical requirements that the team can execute at scale.

  • Own the long-term vision for our ML infrastructure, including deployment, monitoring and MLOps practices. Ensure that all data products are not only performant but also maintainable and compliant with global safety standards.

  • Guide the professional growth of your direct reports, ensuring they are challenged by the right problems and supported by clear career trajectories.

  • Champion the adoption of new technologies (e.g., LLMs, graph databases) and best practices that keep PayJoy at the forefront of financial ML without sacrificing stability.


Requirements
  • PhD or master’s in Computer Science, Statistics, Engineering or a related field

  • 8+ years of hands-on experience in Data Science or ML Engineering, with at least 4+ years in a leadership role managing senior-level or staff-level engineers.

  • A proven track record of designing and delivering large-scale ML systems. You must have a deep understanding of the full ML lifecycle (from feature extraction to production monitoring) and the ability to review system designs and architecture at a high level.

  • Ability to identify bottlenecks in global ML operations and design systematic solutions. You think in terms of platforms, not just individual models.

  • Exceptional ability to communicate complex technical concepts to non-technical stakeholders. You can defend technical decisions to executive leadership and advocate for the "engineering mindset."

PayJoy is proud to be an Equal Employment Opportunity employer and we welcome and encourage people of all backgrounds. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
 
PayJoy Principles
 
Finance for the next billion * Ownership * Break Through Walls * Live Communication * Transparency & Directness * Focus on Scale * Work-Life Balance * Embrace Diversity * Speed * Active Listening

HQ

PayJoy San Francisco, California, USA Office

655 4th St, San Francisco, CA, United States, 94107

Similar Jobs

16 Days Ago
Hybrid
Palo Alto, CA, USA
Expert/Leader
Expert/Leader
Financial Services
Leads hands-on architecture and implementation of production-grade generative AI systems, including search, conversational AI, and agentic workflows. Designs retrieval pipelines, orchestration, dialogue management, and scalable backend systems while optimizing latency, reliability, observability, cost, and evaluation. Serves as the senior technical authority for LLM-powered applications, establishes engineering standards, conducts design and code reviews, mentors engineers, and partners with product and business stakeholders. The role requires deep software engineering, AWS, distributed systems, and regulated-environment experience.
Top Skills: Amazon Web Services (Aws)APIsDistributed SystemsEmbeddingsGenerative AiHybrid SearchKnowledge GraphsLarge Language Models (Llms)MicroservicesPythonRe-RankingRetrieval-Augmented Generation (Rag)
21 Days Ago
Hybrid
San Francisco, CA, USA
245K-336K Annually
Senior level
245K-336K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Leads product strategy and a product management team for enterprise AI/ML and machine learning platforms. Defines Generative AI and ML platform vision, evolves capabilities for data scientists and software developers, drives platform adoption, and partners with adjacent platform leaders on an integrated ecosystem. The role requires deep technical expertise in AI/ML infrastructure, Generative and Agentic AI, cloud and open-source technologies, people leadership, and AI risk management.
Top Skills: Agentic AiAWSGenerative AiKubernetesLangchainMachine LearningPublic CloudRaySpark
One Month Ago
Hybrid
Palo Alto, CA, USA
Senior level
Senior level
Financial Services
Lead end-to-end applied AI/ML solutions for payments trust & safety, from problem framing and data strategy through production deployment, monitoring, and iteration. Drive technical direction, evaluation metrics, reproducibility, and compliance-ready documentation while partnering across product, engineering, data, risk, and compliance stakeholders.
Top Skills: Amazon Web Services (Aws)SparkCi/CdComputer VisionDocument ExtractionGraph Neural NetworksInformation ExtractionMlops (Model RegistryNlpObservability)Optical Character Recognition (Ocr)PythonPyTorchReal-Time / Event-Driven ArchitecturesSQLTensorFlowText ClassificationTransformers

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account