Weights & Biases is hiring a
Machine Learning Engineer

Summary

The job is for a Korean-speaking Machine Learning Engineer - Customer Success at Weights & Biases. The role involves helping customers solve complex machine learning problems, improving their workflow, collaborating on projects, and educating them on best practices. The employee will work with ML teams across various industries.

Requirements

• 2-3 years of relevant experience in a similar role
• Fluent in Korean with business level Japanese and English
• 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
• Ability to travel up to two weeks a month

Responsibilities

• Be an expert in implementing effective, robust, and reproducible machine learning pipelines for 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

Preferred Qualifications

• 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 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)