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At a glance
Job overview
Fundamental is hiring a DevOps Engineer. Fundamental is an AI company developing the world’s most powerful Large Tabular Model to enable enterprise decision‑making. The role offers the chance to tackle technical challenges in foundation model development, building cloud infrastructure, and supporting Fortune 100 customers with AI‑driven solutions.
Key focus areas include Design and implement cloud infrastructure from the ground up, Build and maintain Kubernetes clusters optimized for GPU workloads and ML applications, and Implement GitOps practices using ArgoCD for continuous deployment.
Successful candidates bring 5+ Years Cloud Infrastructure And DevOps Experience and 3+ Years Python Experience. Important skills include AWS, GCP, Kubernetes, Multi-Cluster Management, GPU Workload Optimization, and Resource Scheduling. Preferred (not required): Argo CD, ML Workflow Tooling, MLflow, and Kubeflow.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
About Fundamental Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS – the world's most powerful Large Tabular Model (LTM) – purpose-built for the structured records that actually drive enterprise decisions. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by 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.
Key responsibilities
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Design and implement cloud infrastructure from the ground up
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Build and maintain Kubernetes clusters optimized for GPU workloads and ML applications, as well as Production SaaS hosting
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Implement GitOps practices using ArgoCD for continuous deployment
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Develop infrastructure as code using Terraform
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Create and maintain CI/CD pipelines for infrastructure and application deployment
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Implement monitoring and observability solutions for distributed systems
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Automate infrastructure management with Python and Bash
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Collaborate with ML engineers to optimize infrastructure for model training and serving
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Implement and maintain cost optimization strategies (FinOps) for cloud resources
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Monitor and optimize cloud spending, especially for GPU-intensive workloads
Must have
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5+ years of experience in cloud infrastructure and DevOps
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3+ years of experience with Python
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Strong experience with AWS and GCP cloud platforms
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Deep expertise in Kubernetes, including multi-cluster management, GPU workload optimization, resource scheduling and autoscaling, and network policies and security
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Experience with GitOps tools (ArgoCD preferred)
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Extensive experience with cloud networking, including VPC design, load balancer configuration, network security and segmentation, and cross-cloud networking solutions
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Strong CI/CD expertise, preferably with GitHub Actions
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Proficiency in infrastructure as code (Terraform)
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Experience with monitoring and observability tools
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Experience with FinOps practices and cloud cost optimization
Nice to have
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Experience with ML workflow tooling (MLflow, Kubeflow, or similar)
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Experience with FastAPI and Backend applications
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Familiarity with data platforms like Databricks or Snowflake
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Exposure to SRE practices or cloud security certifications
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Hands-on experience with Prometheus, Grafana, or Datadog
Benefits
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Competitive compensation with salary and equity
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Comprehensive health coverage for you and your dependents
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Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
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Relocation support for employees moving to join the team in one of our office locations
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A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
You've read the whole posting — now see how you match it.