United States onlyAn ideal Solutions Architect will own customer deployments in various cloud infrastructures and/or on-prem reporting to the SA team lead. Helps with debugging when issues come up in the deployments and articulate best practices for using W&B effectively. An SA at W&B would also be responsible for writing blog posts, updating documentation and building internal enablement material for rest of the SA team and other functions of the CS team.
The Solutions Architect will partner closely with Support, Product and Engineering teams internally to influence product roadmap based on customer feedback.
Responsibilities
- Work with our customer's operations team to provision W&B services in Dedicated Cloud, Private cloud, and on-prem environments.
- Work through a multitude of complex infrastructure implementations partnering with highly skilled client engineers.
- Debug customer installations when things aren't working properly.
- Be an expert in implementing effective, robust, and reproducible machine learning pipelines for ML-heavy engineering teams using Weights & Biases tools.
- Partner with our customers to uncover their desired outcomes and be the trusted advisor to help them realize the full potential of W&B in solving their problems.
- Provide customer training sessions, product demos, and workshops covering best practices & different solutions W&B offers to drive adoption when required.
- Partner with Success Machine Learning Engineers to create processes for the post-sales lifecycle (Onboarding/Training, Adoption, Workshops, Demos, etc.)
- Collaborate closely with Support, Product and Engineering teams to influence product roadmap based on customer feedback.
- Partner with the sales engineering team to ensure a smooth transition from POC to when a new customer is onboarded.
Requirements
- A track record of systematically documenting issue in the debugging process to reduce the time to solve future implementations.
- Prior technical customer-facing experience
- Hands-on experience with Docker, Kubernetes, networking, and cloud-managed services such as MySQL and Object Stores.
- Strong fundamentals of using IaC tools preferably Terraform
- Experience with at least one preferably multiple cloud platforms (ex: AWS, GCP, Azure).
- SaaS, Web service / distributed system operations experience.
- Basic proficiency in Python and eagerness to help customers who are primarily users of Python deep learning frameworks and tools be successful.
- Strong Linux/Unix command line experience.
- Excellent communication and presentation skills, both written and verbal.
- Ability to effectively manage multiple conflicting priorities, respond promptly and manage time effectively in a fast-paced, dynamic team environment.
- Ability to break down complex, ambiguous problems and resolve them through customer consultation and execution.
Strong Plus
- Proficiency with Terraform for infrastructure management.
- Proficiency in Kubernetes design patterns like Operator.
- Experience with data engineering and MLOps tooling.
- Interest in being an ML educator and/or building and executing customer training sessions, product demos and/or workshops at a SaaS company.
Our Benefits
- 🏝️ Flexible time off
- 🩺 Medical, Dental, and Vision for employees and Family Coverage
- 🏠 Remote first culture with in-office flexibility in San Francisco
- 💵 Home office budget with a new high-powered laptop
- 🥇 Truly competitive salary and equity
- 🚼 12 weeks of Parental leave (U.S. specific)
- 📈 401(k) (U.S. specific)
- Supplemental benefits may be available depending on your location
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