DevOps Engineer
Fundamental
DevOps Engineer
Fundamental
Predictive analytics platform for structured data
Fundamental is an AI research lab pioneering the future of enterprise decision-making. Our flagship model, NEXUS is the world's most powerful Large Tabular Model (LTM) - purpose-built for the structured records that contain trillions of dollars in business value. With $275m in funding from leading investors and trusted by Fortune 100 companies, Fundamental is giving businesses the Power to Predict.
At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.
Design and implement cloud infrastructure from the ground up
Build and maintain Kubernetes clusters optimized for GPU workloads and ML applications, as well as Production SaaS hosting
Implement GitOps practices using ArgoCD for continuous deployment
Develop infrastructure as code using Terraform
Create and maintain CI/CD pipelines for infrastructure and application deployment
Implement monitoring and observability solutions for distributed systems
Automate infrastructure management with Python and Bash
Collaborate with ML engineers to optimize infrastructure for model training and serving
Implement and maintain cost optimization strategies (FinOps) for cloud resources
Monitor and optimize cloud spending, especially for GPU-intensive workloads
5+ years of experience in cloud infrastructure and DevOps
3+ years of experience with Python
Strong experience with AWS and GCP cloud platforms
Deep expertise in Kubernetes, including multi-cluster management, GPU workload optimization, resource scheduling and autoscaling, and network policies and security
Experience with GitOps tools (ArgoCD preferred)
Extensive experience with cloud networking, including VPC design, load balancer configuration, network security and segmentation, and cross-cloud networking solutions
Strong CI/CD expertise, preferably with GitHub Actions
Proficiency in infrastructure as code (Terraform)
Experience with monitoring and observability tools
Experience with FinOps practices and cloud cost optimization
Experience with ML workflow tooling (MLflow, Kubeflow, or similar)
Experience with FastAPI and Backend applications
Familiarity with data platforms like Databricks or Snowflake
Exposure to SRE practices or cloud security certifications
Hands-on experience with Prometheus, Grafana, or Datadog
Competitive compensation with salary and equity
Comprehensive health coverage for you and your dependents
Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
Relocation support for employees moving to join the team in one of our office locations
A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
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.
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