Solution Architect - US (Remote)
Weights & Biases
- San Francisco, CA
- Permanent
- Full-time
- 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.
- 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.
- 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.
- 🏝️ 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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