Job
Source description available
Source: Zyphra (ashby) · A retrieval date records when our system last obtained the source record. It does not guarantee the vacancy is still open or that every detail has been independently checked.
Description from the source
The source description is formatted below for discovery. The provider owns the original wording and may change its requirements or close applications.
EmploymentFull-time
Overview
The Role:
Full job description
The Role: As a Machine Learning Systems Administrator / DevOps Engineer, you will maintain and build the core infrastructure behind both our model training and our inference cloud. You’ll split your time between our large-scale training clusters and the deployments and services that run our models in production on heterogeneous compute, which spans multiple accelerator types and vendors. You’ll work closely with our training, inference, and product teams to keep these systems reliable, secure, and fast. You’ll also lay the groundwork for workflows that can scale with us. You’ll Work Across: Training clusters
- Administration and automation of our Linux-based cluster environments
- User onboarding/offboarding, access control, and security auditing
- Monitoring system resources, job scheduling, and cluster health
- Bring-up and validation of new hardware (compute, networking, storage)
- Supporting and improving developer workflows (e.g., VSCode remote development, Docker)
- Enabling and supporting large-scale training jobs Inference cloud
- Deploying, operating, and scaling inference services across heterogeneous accelerators
- Managing container orchestration, CI/CD, and rollout pipelines for model deployments
- Building observability for production services, including metrics, logging, alerting, and dashboards
- Owning service reliability: uptime, incident response, and postmortems
- Capacity planning, autoscaling, and utilization/cost tracking across hardware types
- Securing production systems through secrets management, network policy, and tenant isolation You’ll own critical systems end to end. Your work will directly affect developer productivity, training throughput, and the performance and reliability of our inference platform. What We’re Looking For / Requirements:
- Experience with Linux system administration, user and access management, and automation
- Demonstrated expertise in scripting languages for system tooling and automation (bash, Python, etc.)
- Experience with containers (Docker) and scheduling/orchestration systems (Slurm, Kubernetes)
- Experience running production services, including monitoring and alerting (e.g., Prometheus, Grafana), deployment pipelines, and incident response
- Experience building tooling for cluster validation and reliability (accelerator, networking, and storage health checks)
- Experience setting up and managing developer tools and third-party services (e.g., cloud storage providers, Docker Hub, Slack, Gmail, Telegraf, experiment trackers)
- Excellent debugging and troubleshooting skills across compute, storage, and networking
- Strong communication skills and ability to collaborate across technical and non-technical teams Qualifications / Additional Skills:
- Experience with infrastructure as code (e.g., Ansible, Terraform)
- Prior work supporting ML/AI infrastructure, including GPU management and workload optimization
- Experience deploying and operating LLM serving stacks (e.g., vLLM, SGLang, Ray)
- Experience with multiple accelerator platforms (e.g., NVIDIA CUDA, AMD ROCm, TPUs)
- Experience with high-performance networking (InfiniBand, RoCE) and distributed storage
- Experience working with cloud platforms such as AWS, Azure, or GCP
- Familiarity with Apptainer and with integrating containers into Slurm and Kubernetes Why Work at Zyphra:
- Our research methodology is grounded in methodical, step-by-step approaches to ambitious goals. Both deep research and engineering excellence are equally valued
- We strongly value new and crazy ideas and are very willing to bet big on new ideas
- We move as quickly as we can; we aim to minimize the bar to impact as low as possible
- We all enjoy what we do and love discussing AI Benefits and Perks:
- Comprehensive medical, dental, vision, and FSA plans
- Competitive compensation and 401(k) plan
- Relocation and immigration support on a case-by-case basis
- In-office snacks and meals provided
- Unlimited PTO and company holidays
- In-person team in San Francisco with a collaborative, high-energy environment
Tips for this job
Practical JobOpportunity guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
Original authoritative source
JobOpportunity.info helps you discover and organize source listings. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
Apply through JobOpportunity →Browse current JobOpportunity listings from Zyphra (ashby) →
