About the Company

Founded in 2009, Zest AI is transforming the $17 trillion U.S. consumer credit market through AI-driven technology that helps lenders identify creditworthy borrowers overlooked by traditional methods. Our platform enables financial institutions of all sizes to harness AI to improve underwriting accuracy, expand credit access, and deliver better lending experiences. With more than 600 active AI models and over 50 issued and pending patents, Zest AI provides solutions across marketing, underwriting, fraud detection, and lending intelligence. Headquartered in Los Angeles, Zest AI partners with financial institutions to make smarter lending decisions while strengthening the resilience of the U.S. financial system. At Zest AI, we tackle complex challenges that make a meaningful impact on people’s daily lives. Our technical teams build software that enhances consumer financial lending by optimizing credit underwriting decisions. Our mission is to broaden access to equitable lending by leveraging machine learning and large-scale data to redefine traditional credit scoring.

About the Role

The Modeling & Analytics Strategy Team focuses on building the automation backbone behind underwriting and expanding into adjacent domains such as fraud modeling. The team translates advanced modeling strategies into scalable, low-touch, high-impact systems that operate across diverse datasets and products.

Responsibilities

• Scale Up: Build resilient, reusable automation systems across datasets and products
• Optimize Client Models: Deliver consistent, measurable performance improvements through automated workflows
• Innovate with Intelligence: Leverage emerging technologies (e.g., LLMs, agentic tooling) to enhance automation and productivity
• Own ML Systems End-to-End: Design, build, and deploy scalable ML systems from prototype through production
• Take ownership of key services within the modeling automation platform
• Build & Scale Automation Infrastructure: Develop pipelines for client data ingestion, processing, and model delivery
• Design reusable frameworks that scale across products and use cases
• Implement CI/CD pipelines for model packaging, testing, and deployment
• Develop Client-Configurable Systems: Build flexible workflows that adapt to varying client data schemas
• Automate iteration and optimization of client-specific models
• Enable systems to generalize across heterogeneous datasets with minimal manual intervention
• Platform Engineering & Tooling: Contribute to internal tools connecting analytics workflows to production systems
• Drive best practices in code quality, system design, and repository management
• Work within and optimize AWS-based infrastructure
• Cross-Functional Collaboration: Partner with Product, Data Science, and GTM teams to integrate automation into products
• Translate business requirements into scalable technical solutions
• Applied Innovation: Explore practical applications of LLMs and agentic AI to improve productivity
• Evaluate new technologies pragmatically, prioritizing impact over novelty
• Mentorship & Technical Leadership: Mentor junior engineers through design reviews and code feedback
• Help raise engineering standards without formal people management responsibilities

Qualifications

• MS or PhD in Computer Science, Engineering, Physics, or a related quantitative field
• 2+ years of experience building production-grade ML systems

Required Skills

• Strong programming skills in Python

Solid foundation in:

• Machine learning algorithms (tree-based models, neural networks, optimization)
• Statistics, feature engineering, and evaluation methodologies
• Systems & infrastructure experience: Experience building and maintaining:
• Data pipelines and ML automation systems
• CI/CD pipelines for machine learning models

Familiarity with

• AWS or similar cloud environments
• Performance considerations (CPU/GPU, memory, I/O)
• Software engineering excellence: Strong understanding of modular design and object-oriented programming
• Experience with version control and repository management best practices
• Ability to write clean, maintainable, production-quality code

Preferred Skills

• Experience with LLMs or agent-based systems
• Contributions to open-source or research (e.g., GitHub, arXiv)

Perks and benefits

All Zestys experience:

• The opportunity to join a mission-focused company
• People – the best part of Zest
• Robust medical, dental and vision insurance plans
• Annual bonus plan participation
• 401(k) with generous match
• Employee Awards and Recognition
• 11 company holidays
• Winter break (office closed between Christmas and New Year's Day)
• Unlimited vacation time
• Employee Resource Groups
• Generous family leave policy (12 week maternity leave / 6 week paternity leave)
• Phone, internet, wellness, and professional development allowances
• Employee gatherings, including Town Hall meetings

Additionally, our Burbank, CA hybrid Zestys enjoy:

• Beautiful, modern, dog-friendly office with lounge areas, video games, and gigantic jigsaw puzzles
• Daily catered lunches from LA’s best restaurants and a fully stocked kitchen
• Complimentary manicures, pedicures, and mindfulness sessions
• Company happy hours, social events, outings, and much more!

About Zest AI:

Creating a diverse and inclusive culture where all are welcomed, valued, and empowered to achieve our full potential is important to who we are and where we’re headed in the future. We know that unique backgrounds, experiences, and perspectives help us think bigger, spark innovation, and succeed together. Zest is committed to diversity, equity, and inclusion and encourages professionals from underrepresented groups in technology and financial services to apply.

Our core values are Communication, Collaboration, Bias for Action, Client-centricity, and Heart. Learn more at Zest.ai, follow us on LinkedIn (linkedin.com/company/zest-ai/) or Twitter @Zest_AI, or check out our Insights blog (https://www.zest.ai/cms/insights).