Description
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).
We’re hiring an AI Solutions Engineer, Post-Sales to help customers solve real-world problems by enabling them to implement and scale ML pipelines and agentic workflows using Weights & Biases. In this role, you’ll collaborate with engineering teams to ensure smooth onboarding and adoption, act as a trusted advisor on best practices, and represent the voice of the customer internally.
You will partner directly with leading AI teams to optimize workflows, share technical expertise, and influence our product roadmap based on real-world customer feedback.
This is an ideal opportunity for ML practitioners who are customer-focused and eager to work with top AI companies globally.
Responsibilities
- Collaborate with engineering teams to ensure smooth onboarding and adoption of Weights & Biases
- Act as a trusted advisor on best practices for implementing and scaling ML pipelines and agentic workflows
- Represent the voice of the customer internally and influence our product roadmap based on real-world customer feedback
- Partner directly with leading AI teams to optimize workflows and share technical expertise
Requirements
- 3–5 years of relevant experience in a similar role
- Strong programming proficiency in Python
- Hands-on experience enabling production-grade ML systems, with a focus on training and inference pipelines, experiment tracking, deployment patterns, and observability using deep learning frameworks (TensorFlow/Keras, PyTorch/PyTorch Lightning) and MLOps tooling (e.g. Airflow, Kubeflow, Ray, TensorRT)
- Familiarity with cloud platforms (AWS, GCP, Azure)
- Experience with GenAI/LLMs and related tools (e.g. LangChain/LangGraph, HuggingFace Transformers, Pinecone, Weaviate)
- Strong experience with Linux/Unix
- Excellent communication and presentation skills, both written and verbal
- Ability to break down and solve complex problems through customer consultation and execution
Preferred
- Background in robotics
- TypeScript experience
- Proficiency with Fastai, scikit-learn, XGBoost, or LightGBM
- Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes
- Familiarity with data pipeline tools