
51 - 200 employees
Founded 2024
đ€ Artificial Intelligence
đą Enterprise
âïž SaaS
Artificial Intelligence âą Enterprise âą SaaS
Fundamental is an enterprise AI company that builds large tabular models (LTMs) such as NEXUS, pre-trained on billions of tables to detect patterns and predict outcomes from structured data. The company offers an enterprise-grade predictive analytics platform that can be deployed with minimal code or integrated deeply with cloud partners like AWS, emphasizing privacy, security, and scalability. Born from academic research and backed by major investors, Fundamental targets large organizations seeking to extract foresight from their databases and deploy predictive models at cloud scale.
đ February 26
đȘđș Europe â Remote
â° Full Time
đĄ Mid-level
đ Senior
â DevOps & Site Reliability Engineer (SRE)
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51 - 200 employees
Founded 2024
đ€ Artificial Intelligence
đą Enterprise
âïž SaaS
Artificial Intelligence âą Enterprise âą SaaS
Fundamental is an enterprise AI company that builds large tabular models (LTMs) such as NEXUS, pre-trained on billions of tables to detect patterns and predict outcomes from structured data. The company offers an enterprise-grade predictive analytics platform that can be deployed with minimal code or integrated deeply with cloud partners like AWS, emphasizing privacy, security, and scalability. Born from academic research and backed by major investors, Fundamental targets large organizations seeking to extract foresight from their databases and deploy predictive models at cloud scale.
âą Design and implement cloud infrastructure from the ground up âą Build and maintain Kubernetes clusters optimized for GPU workloads and ML applications, as well as Production SaaS hosting âą Implement GitOps practices using ArgoCD for continuous deployment âą Develop infrastructure as code using Terraform âą Create and maintain CI/CD pipelines for infrastructure and application deployment âą Implement monitoring and observability solutions for distributed systems âą Automate infrastructure management with Python and Bash âą Collaborate with ML engineers to optimize infrastructure for model training and serving âą Implement and maintain cost optimization strategies (FinOps) for cloud resources âą Monitor and optimize cloud spending, especially for GPU-intensive workloads
âą 5+ years of experience in cloud infrastructure and DevOps âą 3+ years of experience with Python âą Strong experience with AWS and GCP cloud platforms âą Deep expertise in Kubernetes, including multi-cluster management, GPU workload optimization, resource scheduling and autoscaling, and network policies and security âą Experience with GitOps tools (ArgoCD preferred) âą Extensive experience with cloud networking, including VPC design, load balancer configuration, network security and segmentation, and cross-cloud networking solutions âą Strong CI/CD expertise, preferably with GitHub Actions âą Proficiency in infrastructure as code (Terraform) âą Experience with monitoring and observability tools âą Experience with FinOps practices and cloud cost optimization
âą Competitive compensation with salary and equity âą Comprehensive health coverage, including medical, dental, vision, and 401K âą Fertility support, as well as paid parental leave for all new parents, inclusive of adoptive and surrogate journeys âą Relocation support for employees moving to join the team in one of our office locations âą A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
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