Flex addresses a critical problem: enabling health and wellness brands to accept HSA and FSA payments online. Backed by First Round, Core VC, and Rethink Capital, the company powers checkout for brands like Equinox, Dermstore, Therabody, and Ultrahuman. The platform verifies product eligibility in real time, manages split payments, and issues Letters of Medical Necessity at checkout. With $150 billion in annual HSA/FSA spending potential, Flex unlocks new revenue opportunities for merchants and simplifies benefit usage for consumers.
The company seeks a Data Engineer to design and operate the data and machine-learning systems that determine HSA/FSA eligibility at scale: the pipelines, models, and APIs that turn raw merchant catalogs into structured, classified, decision-ready data at checkout. You'll partner with backend, product, and operations stakeholders to build the systems that move every eligibility decision Flex makes.
This role suits those thriving in ambiguity, taking initiative, and excited about building at an early-stage company.
Design, build, and own the data pipelines and ML services that classify product eligibility and power downstream decisions across Flex
Model the data domain (products, merchants, eligibility rules, classifications, and outcomes) in warehouses and serving systems other teams build on
Partner with backend, product, and operations stakeholders translating merchant and consumer needs into reliable data products, models, and APIs
Own and improve the architecture of the data warehouse, transformation layer, ML training and inference systems, and real-time serving paths
Analyze, troubleshoot, and resolve production issues rooted in data quality, model accuracy, pipeline reliability, and serving latency
Collaborate on cross-functional projects connecting the full Flex experience, from consumer checkout to merchant analytics
Build and maintain evaluation harnesses, golden datasets, and observability for the models and pipelines you ship
Create and maintain documentation for data models, pipelines, and on-call runbooks
Contribute to a culture of learning, problem-solving, and operational excellence
5+ years building production data systems and pipelines in Python or a comparable typed language
Strong SQL and data-modeling fundamentals; experience with a modern cloud warehouse (Snowflake, BigQuery, Redshift, or similar) and a transformation framework like dbt
Hands-on experience deploying machine-learning models to production, owning training, inference, evaluation, and rollout, not just notebooks
Familiarity with at least one transformer-based ML framework (PyTorch + Hugging Face Transformers preferred) and a working sense of when classical or embedding-based models beat LLMs and when they don't
Resourceful, curious, and comfortable learning new tools quickly
Thrive in fast-paced, dynamic environments and enjoy wearing multiple hats
Collaborative and enjoy working across teams to solve problems
Execution mindset with focus on end users
Proficient at leveraging AI tools to ship faster
Experience with serverless compute platforms for data and ML workloads (Modal, Ray, AWS Lambda, GCP Cloud Run, or similar)
Production experience with vector databases and embedding-based retrieval
Self-hosted LLM inference experience (vLLM, TGI, SGLang) and a working sense of GPU economics
Background in payments, fintech, or health benefits (HSA/FSA), or another regulated, money-moving domain
Experience building or maintaining a golden-dataset evaluation harness for an ML system
Comfort reading and contributing to a Rust-based backend that consumes your APIs
A mission-driven team making healthcare spending effortless
Early-stage impact: your work directly shapes growth and success
Collaborative, high-trust, and transparent culture
Competitive compensation and equity package
Flexible, remote-friendly work environment
Salary: $160K to $220K
Equity: Offers Equity
Additional Benefits:
Medical, dental, and vision plans
Unlimited PTO and sick days
Paid parental leave
Flexible, remote-first environment
Flex is an equal opportunity employer encouraging applicants from all backgrounds and life experiences. The company celebrates diversity and does not discriminate based on race, religion, color, national origin, sexual orientation, gender identity, gender expression, age, veteran status, disability status, or any other legally protected characteristic.
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