技术支持工程师(推理)- 美国周末
Technical Support Engineer (Inference) - US Weekends
职位描述
作为一家开创性AI公司的技术支援工程师,你将作为第一道防线,支持客户在Together AI平台上构建训练、微调和推理解决方案。你需要深入解决复杂的工程技术问题,提供快速有效的解决方案,同时担任产品专家。作为客户体验团队的一员,你将与产品和销售团队紧密合作,推动我们产品的持续改进。这是一个为对AI和客户成功充满热情的资深技术人员提供的激动人心的机会,在快节奏、创新的环境中发挥重大影响。
工作时间
- 这是一个全职岗位,需在美东时间白天工作。该职位需要在周末(周六和周日)以及另外两个工作日工作。
- 该职位为4天工作制,每天10小时,周六和周日还需额外2小时的待命值班。
- 该职位最初为周一至周五的工作安排,以便于熟悉工作并从同事处学习。在被认为完全熟悉后,该职位将转为4天工作制的周末班次。
职责
- 直接与客户互动,解决涉及我们前沿GPU集群以及推理和微调服务的复杂技术问题;确保每次都能快速有效地解决问题。
- 作为面向客户的SRE,确保客户的推理端点(运行在Kubernetes上)保持健康、稳定和高性能。
- 成为我们所有生成式AI解决方案的产品专家,成为在问题升级到工程和产品团队之前的最后一道技术防线。
- 在硬件和平台迁移过程中提供协助,验证系统健康状况和流量路由。监控仪表盘以检测异常,并通过数据驱动的分析进行升级。
- 在事件和性能下降期间管理面向客户的沟通;将深度技术发现(延迟退化、供应商问题、网络可达性下降)转化为清晰、有证据支持的更新,同时不暴露平台内部信息。
- 为模型部署、容量重新平衡和集群配置贡献基础设施变更。你将通过拉取请求(基础设施即代码)执行基础设施变更,例如端点配置、模型上线/下线和容量扩展。
- 标记引擎级别的错误,并附上日志和复现步骤供工程团队处理。
查看英文原文
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 GPU clusters and our inference and fine-tuning services; ensure swift and effective solutions every time.
- Act as a customer facing SRE to ensure our customer’s Inference endpoints (running on Kubernetes) remain healthy, stable, and performant
- Become a product expert in all of our Gen AI solutions, serving as the last line of technical defense before issues are escalated to Engineering and Product teams.
- Assist with hardware and platform migrations by validating system health and traffic routing. Monitor dashboards to detect anomalies and escalate with data-backed analysis
- Manage customer-facing communications during incidents and degradations; translate deep technical findings (latency regressions, provider issues, network reachability drops) into clear, evidence-backed updates without exposing platform internals
- Contribute infrastructure changes for model deployment, capacity rebalancing, and cluster configuration. You will execute infrastructure changes via pull requests (infra-as-code) for tasks such as endpoint configuration, model bringup/bringdown, and capacity scaling
- Flag engine-level bugs with logs and reproduction steps for engineering
- 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
- 6+ years of experience in a customer-facing technical role, SRE, DevOps, or infrastructure engineering, with at least 1 year in a support role for an AI service
- 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, production-level experience with infrastructure services (e.g., Kubernetes, SLURM), infrastructure as code solutions (e.g., Ansible) high-performance network fabrics, NFS-based storage management, and container infrastructure
- Familiarity with operating storage systems in HPC environments such as Vast and Weka
- Proven ability to diagnose complex network-layer issues and read traces
- Strong knowledge of Python, TypeScript, and/or JavaScript with testing/debugging experience using curl and Postman-like tools
- Demonstrated expertise with observability tooling (e.g., Prometheus, Grafana) at scale
- Deep familiarity with REST API debugging and HTTP semantics
- Experience with LLM inference frameworks and LoRA fine-tuning and common training failure modes
- Experience with Infrastructure as Code and Git-based workflows
- Background in GPU cluster management
- Cloud platform experience (AWS, GCP, and/or Azure)
- 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