How much experience is required?

At least 5 years of relevant experience for this DevOps Engineer role.

What's the tech stack?

Joblaze extracted these technologies from the posting: AWS, ArgoCD, CI/CD, Datadog, FinOps, GCP.

What seniority level is this role?

Fundamental targets senior candidates for this position.

Is this full-time or contract?

Full-time for this DevOps Engineer role at Fundamental.

Joblaze summary

In this role, the DevOps Engineer at Fundamental is responsible for designing and implementing cloud infrastructure, focusing on optimizing Kubernetes clusters for machine learning applications. Key skills include extensive experience with AWS and GCP, proficiency in Python, and a strong grasp of GitOps practices, particularly with ArgoCD. This position is ideal for seasoned professionals with over five years in cloud infrastructure and DevOps, who are eager to tackle complex technical challenges in a pioneering AI company.

Joblaze insights

Listed 9 days ago on Joblaze — tracked directly from Fundamental's career page.
Fundamental has 17 other open roles including MLOps Team Lead, Full-Stack Engineer, Solutions Architect.
6527 active Python roles on Joblaze right now.
2727 active AWS roles on Joblaze right now.
2568 active Kubernetes roles on Joblaze right now.
Typical Python salary we track runs $125,000–$190,800 (median $160,000, across 3229 roles). See Python salary trends

Quick facts

How much experience is required?: At least 5 years of relevant experience for this DevOps Engineer role.
What's the tech stack?: Joblaze extracted these technologies from the posting: AWS, ArgoCD, CI/CD, Datadog, FinOps, GCP.
What seniority level is this role?: Fundamental targets senior candidates for this position.
Is this full-time or contract?: Full-time for this DevOps Engineer role at Fundamental.

From the original posting

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

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

Must have

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

Nice to have

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

Benefits

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