Senior MTS, Infrastructure

Clera

Zürich, Switzerland

On-site

Who this role is best for

Geared toward infrastructure engineers comfortable with distributed systems and cloud compute, this role suits candidates with deep operational experience in production environments and a background in AI research.

Best fit for

Infrastructure engineers with 5 to 10+ years of experience in production systems and cloud platforms
— “5 to 10+ years of relevant experience building or operating infrastructure and production systems.”
Candidates who have shaped distributed workflow scheduling and cost optimization strategies
— “Design and optimize distributed workflow scheduling to improve performance and control costs.”
Individuals with a history of improving monitoring and diagnostic systems for reliability
— “Improve monitoring, logging, and diagnostic tools so the team can identify and resolve system failures quickly.”

Things to consider

On-site presence in Zürich is mandatory, which may require relocation or visa planning
— “On-site in Zürich, Switzerland.”
The role demands balancing reliability, complexity, and cost in production environments
— “Experience investigating production issues and balancing reliability, complexity, and cost.”

How to stand out

Highlight your experience in cloud compute and distributed systems optimization in your resume
— “Build and operate cloud compute infrastructure for large-scale research workloads.”
Emphasize your background in developing recovery procedures and preventing duplicate work
— “Develop recovery procedures for worker interruptions, application crashes, and partial results while preventing duplicate work.”
Showcase your proficiency with infrastructure as code and monitoring platforms like Prometheus
— “Familiarity with infrastructure as code tools such as Terraform and monitoring platforms such as CloudWatch, Prometheus, or Grafana.”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

design and optimize distributed workflow scheduling
improve monitoring and diagnostic tools
partner with researchers and engineers to develop new platform capabilities

Typical background

5 to 10+ years of relevant experience building or operating infrastructure and production systems

Skills & requirements

Required

Cloud InfrastructureDistributed SystemsLinuxPythonAWS

Preferred

TerraformCloudwatchPrometheusGrafanaVirtualizationVM ImagesBatch SchedulingExperiment OrchestrationSandboxing Untrusted Code

Stack & domain

PythonLinuxAWSTerraformCloudwatchPrometheusGrafanaVirtualizationVM ImagesSnapshotsDesktop Application AutomationBatch SchedulingExperiment OrchestrationSandboxing Untrusted Code

About the role

Original posting from Clera via Ashby

ABOUT THE ROLE
Join the engineering team at an AI research infrastructure startup to design, build, and scale the systems that support research workloads. You will own key infrastructure capabilities across cloud compute, distributed systems, storage, and experiment orchestration, helping improve reliability, performance, and resource efficiency as the platform grows.
WHAT YOU'LL DO
Build and operate cloud compute infrastructure for large-scale research workloads.
Design and optimize distributed workflow scheduling to improve performance and control costs.
Develop recovery procedures for worker interruptions, application crashes, and partial results while preventing duplicate work.
Improve monitoring, logging, and diagnostic tools so the team can identify and resolve system failures quickly.
Partner with researchers and engineers to develop new platform capabilities and shape the underlying architecture.
WHAT WE'RE LOOKING FOR
5 to 10+ years of relevant experience building or operating infrastructure and production systems.
Strong Python and Linux skills, including scripting, process management, and debugging.
Experience operating services on AWS or another major cloud platform, including compute, storage, networking, and access management.
Understanding of distributed systems concepts such as queues, timeouts, retries, idempotency, and duplicate request handling.
Experience investigating production issues and balancing reliability, complexity, and cost.
Familiarity with infrastructure as code tools such as Terraform and monitoring platforms such as CloudWatch, Prometheus, or Grafana.
Experience with virtualization, VM images and snapshots, desktop application automation, batch scheduling, experiment orchestration, or sandboxing untrusted code is a plus.
COMPENSATION & BENEFITS
Competitive compensation and equity are offered. Visa sponsorship is available.
LOCATION
On-site in Zürich, Switzerland.

Source: Clera careers (Ashby)