--- title: 'Machine Learning Systems Administrator / DevOps Engineer: Training Clusters & Inference Cloud at Zyphra' canonical: 'https://feeny.ai/job/machine-learning-systems-administrator-devops-engineer-training-clusters-54x9wakr7cjb' type: 'job' last_seen: '2026-10-18' --- # Machine Learning Systems Administrator / DevOps Engineer: Training Clusters & Inference Cloud at Zyphra - **Company:** Zyphra - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-10-15 - **Last confirmed live:** 2026-10-18 - **Apply:** https://jobs.ashbyhq.com/zyphra/7531f714-8809-498b-9bdb-44af16149824 ## 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 ## About Zyphra ## Company Overview - **One-liner**: Zyphra is a full-stack AI company building open foundation models and a sovereign cloud platform to deliver advanced AI to developers, enterprises, and hyperscalers. - **Entity Type**: Private, Series A - **Headquarters**: San Francisco, California, United States - **Founded**: 2020 (some sources cite 2021) - **Founders**: Krithik Puthalath (CEO), Beren Millidge (Chief Scientist), Danny Martinelli (Head of Product), Tomás Figliolia (Chief Architect) ## Core Business - **Primary industry**: Artificial Intelligence / Foundation Models / Cloud AI Infrastructure - **Target customers**: Developers, enterprises, and "frontier AI hyperscalers" (B2B) - **Mission or purpose**: "Open Superintelligence" – to enable sovereign, transparent, and customizable AI that runs on any hardware without vendor lock-in. ## Products & Services - **[Zyphra Research](https://www.zyphra.com/)**: Open-source foundation models trained on heterogeneous compute, focusing on novel architectures for long-term memory, continual learning, and silicon performance. Released as research prototypes. - **[Zyphra Cloud](https://www.zyphra.com/)**: Full-stack AI platform built on AMD, designed for long-horizon agents. Provides managed infrastructure for deploying, customizing, and running Zyphra's or third-party models with full data sovereignty. ## Market Standing - **Valuation/Market Cap**: Not disclosed - **Key Metric**: Total funding of **$11M** (Series A) - **Notable Investors/Partners**: AMD, Intel Capital, Future Ventures, Bison Ventures, Transpose Platform, and others - **Growth Signals**: - Headcount grew **151.9% YoY** to 53 employees - Operates in 5 countries (US, UK, Canada, India, Saudi Arabia) with offices in San Francisco, Palo Alto, and London - Active job postings: 14 (up 16.7% quarterly) - LinkedIn followers grew 236.3% year-over-year ## Competitive Advantages - **Full-stack open-source approach**: Combines novel model architectures (probabilistic computing, heterogeneous compute) with a cloud platform optimized for long-horizon AI agents. - **Hardware agnosticism**: Promises "run intelligence across any hardware and any provider, without lock-in," with early focus on AMD silicon. - **Commitment to openness**: Models are transparent, allowing customers to audit reasoning and adapt to specific domains. - **Sovereignty focus**: Enterprises own their models, data, and deployments – appealing to regulated industries. ## Strategic Focus - **Priority on architecture innovation** (continual learning, long-term memory, silicon performance) over scaling existing methods. - **Building a full-stack platform** that tightly couples research breakthroughs with a production-grade cloud service. - **Scaling the team** aggressively – hiring across research engineering, platform, developer relations, and AI engineering. ## Why Work Here - **Culture of open research**: Employees contribute to novel model architectures that are publicly released, offering a rare blend of academic freedom and product impact. - **Heavy engineering focus**: 57% of the team is in technical roles, with a flat structure (62% specialist-level roles). - **Locations**: San Francisco (HQ) and London, with potential for remote-friendly roles (not explicitly stated). - **Notable perks**: Not detailed publicly, but typical for a well-funded Series A startup (equity, benefits, etc.). - **Growth trajectory**: 150%+ headcount growth signals rapid scaling and career advancement opportunities. ## Sources 1. [zyphra.com](https://www.zyphra.com/) 2. [zyphra.com about](https://www.zyphra.com/about) 3. [jobs.ashbyhq.com/zyphra](https://jobs.ashbyhq.com/zyphra) 4. [linkedin.com/company/zyphra](https://www.linkedin.com/company/zyphra) 5. [cbinsights.com/company/zyphra](https://www.cbinsights.com/company/zyphra) ## Other roles at Zyphra - [Research Engineer -- Vision and Vision-Language Models](https://feeny.ai/job/research-engineer-vision-and-vision-language-models-zyphra-san-francisco-tcb7cvz1g2qx) — San Francisco, CA - [GTM Engineer](https://feeny.ai/job/gtm-engineer-zyphra-san-francisco-036cvpkp3amk) — San Francisco, CA - [Principal Solutions Architect](https://feeny.ai/job/principal-solutions-architect-zyphra-san-francisco-tvmr7yr66sye) — San Francisco, CA - [Developer Relations Lead](https://feeny.ai/job/developer-relations-lead-zyphra-san-francisco-8aak96cd9gcr) — San Francisco, CA - [Research Engineer - Model Architectures](https://feeny.ai/job/research-engineer-model-architectures-zyphra-san-francisco-q2xft42gbdne) — San Francisco, CA - [Research Engineer - Agency and Reasoning](https://feeny.ai/job/research-engineer-agency-and-reasoning-zyphra-san-francisco-n78mrpw38xb2) — San Francisco, CA - [Research Engineer - Language Model Pre-Training](https://feeny.ai/job/research-engineer-language-model-pre-training-zyphra-san-francisco-1e2n0tewvz0d) — San Francisco, CA - [Research Engineer - Audio & Speech Models](https://feeny.ai/job/research-engineer-audio-speech-models-zyphra-san-francisco-vpqsx2qaz8pm) — San Francisco, CA - [Data Engineer - Multimodal Systems](https://feeny.ai/job/data-engineer-multimodal-systems-zyphra-san-francisco-kd4wkewajppq) — San Francisco, CA - [Platform Engineer](https://feeny.ai/job/platform-engineer-zyphra-san-francisco-7nkavn90wn8m) — San Francisco, CA