AI Solutions Engineer, Post Sales Scale - W&B
CoreWeaveAbout the role
What You’ll Do
The Field Engineering team at Weights & Biases plays a vital role in ensuring customer success and adoption of our platform. As part of this team, we partner with Sales, Support, Product, and Engineering to lead technical success after the sales process. We work closely with some of the most advanced AI teams in the world, helping them build, optimize, and scale their ML and GenAI workflows across industries such as computer vision, robotics, natural language processing, and large language models (LLMs).
About the Role
We’re hiring a Post-Sales AI Solutions Engineer (AISE), Scale Customer Success to help customers successfully implement and scale AI/ML workflows and GenAI/agentic applications on Weights & Biases. You will design and deliver technical enablement and adoption programs that reach many customers at once, create reusable assets that improve self-serve success, and use product signals and feedback loops to continuously improve outcomes.
Key Responsibilities
- Run 1-to-many onboarding and enablement programs
Own and deliver scalable onboarding and adoption motions (webinars, cohort sessions, group training, and office hours) that help customers get to value quickly and consistently. - Build reusable technical assets that drive self-serve success
Create and maintain playbooks, reference architectures, templates, sample code/notebooks, and troubleshooting guides that standardize best practices and reduce repeated 1:1 work. - Operate the scaled motion using signals and feedback loops
Use product usage signals and customer patterns to segment and trigger the right interventions, track program impact (activation, time-to-first-value, feature adoption), and feed recurring insights back to Support, Product, and Field Engineering to continuously improve the scaled journey.
Who You Are
- 3–5 years of relevant experience in a similar role
- Strong programming proficiency in Python
- Experience with deep learning frameworks (TensorFlow/Keras, PyTorch Lightning) and tools (e.g., Streamlit, LangChain)
- Familiarity with cloud platforms (AWS, GCP, Azure)
- Excellent communication and presentation skills, both written and verbal
- Organized and outcomes-driven: you can run programs, measure impact, and iterate.
Preferred
- Experience with GenAI and LLMs
- Proficiency with HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, or Ray
- Experience with hyperparameter optimization solutions
- Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes
- Familiarity with data pipeline tools
Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.
- You love collaborating with top AI teams to solve real-world ML and GenAI challenges
- You’re curious about how to optimize AI workflows at scale
- You’re an expert in Python and ML tooling, with a passion for enabling customer success
Why Us?
We work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:
- Be Curious at Your Core
- Act Like an Owner
- Empower Employees
- Deliver Best-in-Class Client Experiences
- Achieve More Together
We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get s
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