At Weights & Biases, our mission is to build the best developer tools for machine learning. Weights & Biases is a series C company with $200 million in funding and a rapidly growing user base. Our platform is an essential piece of the daily work for machine learning engineers, from academic research institutions like FAIR and UC Berkeley to massive enterprise teams including iRobot, OpenAI, Toyota Research Institute, Samsung, NVIDIA, Salesforce, Blue Cross Blue Shield, Lyft, and more.
Reporting to the VP of Customer Success, the Solutions Architect will own customer deployments in various cloud infrastructures and/or on-prem. Help with debugging when issues come up in the deployments and articulate best practices for using W&B effectively.
The Solutions Architect will partner closely with Support, Product and Engineering teams to influence product roadmap based on customer feedback.
Role and Responsibilites
- Work with our customer's operations team to provision W&B services in their 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.
- Effectively articulate best practices for instrumenting machine learning pipelines to our customers as a trusted advisor.
- 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 problem.
- Provide customer training sessions, product demos, and workshops covering best practices & different solutions W&B offers to drive adoption.
- Partner with Customer Success Managers 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 sales engineering team to ensure there's a smooth transition from POC to when a new customer is onboarded.
- A track record of systematically documenting issue in debugging process to reduce the time to solve future implementations.
- Hands-on experience with Docker, Kubernetes, networking and cloud managed services such as MySQL and Object Stores.
- Experience with one or more cloud platforms (ex: AWS, GCP, Azure).
- SaaS, Web service / distributed system operations experience.
- Familiarity with one or more of the following packages: TensorFlow / Keras, PyTorch / PyTorch Lightning.
- 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.
- Familiarity with Terraform for infrastructure management.
- 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 problems and resolve them through customer consultation and execution.
- Proficiency with Terraform for infrastructure management
- Experience with data engineering and MLOps tooling
- Interest in ML frameworks: HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, Ray
- Interest in hyper parameter optimization solutions such as SigOpt, Optuna etc.
- Interest in being an ML educator and/or building and executing customer training sessions, product demos and/or workshops at a SaaS company
Who this role is for
- Passion for machine learning: You understand how exciting the ML space is and how quickly it's growing. You're excited to speak with industry leaders at the forefront of ML research and development
- Outgoing and friendly: You'll love this role if you enjoy connecting with real users every day, helping them adopt the Weights & Biases platform, and answering all of their questions
- Technically Savvy: You enjoy instrumenting models in PyTorch, Keras, and TensorFlow and understand complicated workflows
- Autonomous and adaptable: You understand different companies have different workflows, and you're excited to solve these challenges
- Curious and Driven: You want to understand future customers' ML workflow and prove how Weights & Biases will improve their day-to-day
Why join us?
- Top-tier machine learning teams rely on our tools for their daily work at companies including OpenAI, Toyota Research Institute, Lyft, Samsung, and Pandora.
- You'll never stop learning. This role gives you first-hand experience talking with leading researchers in the field, understanding their problems, and directly shaping the product direction.
- Our experienced founding team has successfully built and sold ML tools in the past at Figure Eight, and their deep knowledge of our industry, empathy for our users, and skillful management is driving W&B to success.
- We're a unicorn! Here's a blog poston what this means for W&B from our co-founder and CEO, Lukas Biewald.
- Customers genuinely benefit from our tool. Here's a quote from Wojciech Zaremba, Cofounder and Robotics Lead, OpenAI: W&B allows to scale up insights from a single researcher to the entire team, and from a single machine to hundreds of them.
- A best-in-class product in one of the fastest-growing and largest market segments
- Unlimited vacation time
- 100% Medical, Dental, and Vision for employees and Family Coverage
- Remote first culture with in-office flexibility in San Francisco
- $500 home office budget with new high-powered laptop
- Truly competitive salary and equity
- 12 weeks of Parental leave
- ?? 401(k)
Weights & Biases
Weights & Biases helps machine learning teams build better models faster. With a few lines of code, practitioners can instantly debug, compare and reproduce their models — architecture, hyperparameters, git commits, model weights, GPU usage, and even datasets and predictions — and collaborate with their teammates.