Pre-Sales Machine Learning Engineer, Customer Success - EMEA (Remote)

February 16

Weights & Biases

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Developer-first MLOps platform.

deep learning • developer tools • machine learning • MLOps

51 - 200

💰 Corporate Round on 2022-05

Description

• Be an expert in implementing effective, robust, and reproducible machine learning pipelines for engineering teams using Weights & Biases tools • Partner with our customers and prospects to uncover their desired outcomes and be the trusted advisor to help them evaluate the full potential of W&B in solving their problem • Effectively articulate W&B product best practices for instrumenting machine learning pipelines to our customers as a trusted advisor • Provide product demos and workshops covering best practices & different solutions W&B offers to establish technical success in the evaluation process • Partner with Account Executives to create processes for the pre-sales lifecycle (POVs, Demos, etc.) • Collaborate closely with Support, Product and Engineering teams to influence product roadmap based on customer feedback

Requirements

• 2-3 years of relevant experience in a similar role • Experience using one or more of the following packages: TensorFlow/Keras, PyTorch Lightning • Strong programming proficiency in Python and eagerness to help customers who are primarily users of Python deep learning frameworks and tools be successful • 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. • Experience with cloud platforms (AWS, GCP, Azure) • Experience with Linux/Unix • Strong plus Proficiency with one or more of the following packages: HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, Ray • Experience with hyperparameter optimization solutions • Experience with data engineering, MLOps and tools such as Docker and Kubernetes • Experience with data pipeline tools • Experience as an ML educator and/or building and executing customer training sessions, product demos and/or workshops at a SaaS company

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 • Explore benefits by country