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Fundamental

Predictive analytics platform for structured data

Full-Stack Engineer

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 5 years of experience in full-stack engineering roles.
  • Strong Python development experience, particularly with FastAPI and the ASGI ecosystem for high-performance API development.
  • Experience building full-stack applications with modern frontend frameworks such as React, Vue, or Angular and backend systems.
  • Proficiency designing event-driven architectures using publish/subscribe messaging patterns and integrating distributed task queues such as Celery for asynchronous processing.
  • Understanding of model serving patterns including REST, gRPC, and asynchronous batching, with experience handling large-scale inference workflows in production.
  • Knowledge of SQL and NoSQL database systems and integration with cloud data platforms such as Snowflake and Databricks.
  • Experience with state management, session persistence, and efficient data flow patterns in distributed applications.
  • Ability to deliver high-quality, maintainable frontend code and collaborate with design and product stakeholders.

Responsibilities

  • Build robust backend services and application programming interfaces for model inference, including efficient batching systems and optimization for large datasets.
  • Implement state management and session persistence mechanisms to maintain model context and deliver consistent user experiences.
  • Design and develop responsive, user-friendly frontends for model interaction, monitoring, and configuration using modern frameworks such as React, Vue, or Angular.
  • Design event-driven architectures with publish/subscribe messaging patterns to enable asynchronous processing and system scalability.
  • Develop database connectivity layers and integration points with third-party data sources such as Snowflake and Databricks.
  • Create comprehensive error handling, retry mechanisms, and monitoring solutions to ensure system reliability.
  • Collaborate with MLOps and DevOps teams to optimize the overall architecture and deployment pipeline.

About the Company

Fundamental

Predictive analytics platform for structured data

Fundamental offers an enterprise-grade predictive intelligence product called NEXUS, a Large Tabular Model that analyzes structured data from spreadsheets, databases, and CRM systems. It learns patterns directly from raw tabular data, eliminating the need for extensive feature engineering, and combines forecasting, classification, anomaly detection, and scenario simulation in one model. NEXUS is deployed through the AWS dashboard via a strategic partnership and was trained on Amazon SageMaker HyperPod to handle datasets with billions of rows, serving industries like financial services, healthcare, retail, and energy with seven-figure contracts for use cases like demand forecasting, price prediction, and churn analysis. The goal is to turn raw data into actionable insights that improve forecasting accuracy, reduce risk, and optimize business outcomes, setting Fundamental apart by focusing on structured data rather than unstructured text or images.

Company size
51-200
Company stage
N/A
Total funding
$255M
Headquarters
San Francisco, CA
Founded
2024

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