Technical Support Engineer (GPU Clusters) - US Weekends

Posted 10 Days Ago
Be an Early Applicant
Hiring Remotely in AUS
Remote
160K-230K Annually
Mid level
Artificial Intelligence • Information Technology
The Role
Provides customer-facing technical support for enterprise GPU clusters, acting as an SRE and product expert. Responsibilities include monitoring cluster health, troubleshooting Kubernetes, Slurm, storage, networking, and hardware issues, maintaining production infrastructure, and coordinating escalations with Engineering, Product, Research, and Sales. The role also documents procedures, identifies recurring support patterns, supports roadmap improvements, and provides weekend, holiday, and occasional on-call coverage.
Summary Generated by Built In
About the role

As a Technical Support Engineer at a pioneering AI company, you'll be the first line of defense to support customers as they build out training, fine tuning, and inference solutions with Together AI. You'll dive deep into complex technical challenges, providing swift and effective solutions while serving as a product expert. As a part of the Customer Experience organization, you will collaborate closely with product and sales, driving continuous improvement of our offerings. This is an exciting opportunity for a deeply technical professional passionate about AI and customer success to make a significant impact in a fast-paced, innovative environment.

Required hours
  • This is a fulltime position working US daytime hours. The role will work both weekend days (Saturday and Sunday) as well as two additional weekdays.
  • This is a 4-day shift, 10 hours per day, with 2 additional hours of on-call coverage on Saturdays and Sundays.
  • The role would start as a Monday to Friday role for the first few months to allow for ramping up and learning from teammates. After being considered fully ramped, the role would transition to the 4-day weekend shift.
Responsibilities
  • Engage directly with customers to tackle and resolve complex technical challenges involving our cutting-edge Kubernetes GPU clusters; ensure swift and effective solutions every time.
  • Act as a customer facing SRE to ensure our customer’s Kubernetes clusters remain healthy and stable
  • Become a product expert in our GPU Cluster service, serving as the last line of technical defense before issues are escalated to Engineering and Product teams.
  • Monitor GPU cluster health and proactively communicate hardware issues to customers (thermal throttling, BMC failures, missing GPUs, and NVLink/InfiniBand degradation) with clear remediation steps
  • Operate and maintain production infrastructure for enterprise GPU customers, including fleet rebalancing, Slurm cluster maintenance, node repair/migration, and Kubernetes-based workload management
  • Investigate and resolve storage and networking issues such as Weka filesystem degradation, InfiniBand link failures, and bandwidth anomalies on bare-metal and VM environments
  • Collaborate seamlessly across Engineering, Research, and Product teams to address customer concerns; collaborate with senior leaders both internally and externally to ensure the highest levels of customer satisfaction.
  • Transform customer insights into action by identifying patterns in support cases and working with Engineering and Go-To-Market teams to drive Together’s roadmap (e.g., future models to support)
  • Maintain detailed documentation of system configurations, procedures, troubleshooting guides, and FAQs to facilitate knowledge sharing with team and customers.
  • Be flexible in providing support coverage during holidays, nights and weekends as required by business needs to ensure consistent and reliable service for our customers.
Requirements
  • 3+ years of experience in a customer-facing technical role with at least 1 year in a support function for an AI service or supporting a mission-critical API in SaaS
  • Experience as an SRE or DevOps engineer working with Kubernetes
  • Strong technical background, with knowledge of AI, ML, GPU technologies and their integration into high-performance computing (HPC) environments.
  • Advanced knowledge with infrastructure services (e.g., Kubernetes, SLURM), infrastructure as code solutions (e.g., Ansible) high-performance network fabrics, NFS-based storage management, container infrastructure, and scripting and programming languages.
  • Experience with HPC/Slurm cluster environments — node draining, job scheduling, maintenance workflows
  • Familiarity with high-speed networking concepts — InfiniBand, RDMA, network interface diagnostics
  • Experience with distributed storage systems (e.g., Weka, NFS) and troubleshooting I/O and bandwidth issues
  • Foundational understanding in the installation, configuration, administration, troubleshooting, and securing of compute clusters.
  • Complex technical problem solving and troubleshooting, with a proactive approach to issue resolution
  • Ability to work cross-functionally with teams such as Sales, Engineering, Support, Product and Research to drive customer success.
  • Strong sense of ownership and willingness to learn new skills to ensure both team and customer success.
  • Excellent communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
  • Ability to operate in dynamic environments, adept at managing multiple projects, and comfortable with frequent context switching and prioritization.
About Together AI

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160K - $230K + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy

Skills Required

  • 3+ years of experience in a customer-facing technical role
  • At least 1 year supporting an AI service or mission-critical SaaS API
  • Experience as an SRE or DevOps engineer working with Kubernetes
  • Strong knowledge of AI, machine learning, GPU technologies, and HPC environments
  • Advanced knowledge of Kubernetes, Slurm, Ansible, high-performance network fabrics, NFS-based storage, container infrastructure, and scripting or programming languages
  • Experience with HPC and Slurm cluster environments, including node draining, job scheduling, and maintenance workflows
  • Familiarity with InfiniBand, RDMA, and network interface diagnostics
  • Experience with distributed storage systems such as Weka or NFS, including I/O and bandwidth troubleshooting
  • Understanding of compute cluster installation, configuration, administration, troubleshooting, and security
  • Complex technical problem-solving and troubleshooting skills
  • Ability to work cross-functionally with Sales, Engineering, Support, Product, and Research
  • Strong ownership and willingness to learn new skills
  • Excellent communication and interpersonal skills, including explaining technical concepts to non-technical stakeholders
  • Ability to manage multiple projects, context switching, and prioritization in dynamic environments

Together AI Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Together AI and has not been reviewed or approved by Together AI.

  • Fair & Transparent Compensation — Pay is considered competitive for the company’s stage, with especially strong offers for technical and research roles. A posted AI researcher range reaching into the high-$200Ks alongside equity and benefits reinforces the overall pay positioning.
  • Equity Value & Accessibility — Equity is commonly included alongside base salary, giving employees ownership exposure tied to company growth. Total compensation is often framed around salary plus equity for specialized roles.
  • Flexible Benefits — Job listings describe a flexible time‑off policy and hybrid or remote work options. Commuter perks and regular team events are also cited as part of the package.

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The Company
HQ: Surry Hills
84 Employees
Year Founded: 2022

What We Do

Together AI is a research-driven artificial intelligence company. We contribute leading open-source research, models, and datasets to advance the frontier of AI. Our decentralized cloud services empower developers and researchers at organizations of all sizes to train, fine-tune, and deploy generative AI models. We believe open and transparent AI systems will drive innovation and create the best outcomes for society

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