Machine Learning Engineer, Customer Success - Japan (Korean Language Requirement)

Tokyo

Weights & Biases

WandB is a central dashboard to keep track of your hyperparameters, system metrics, and predictions so you can compare models live, and share your findings.

View company page

At Weights & Biases, our mission is to build the best developer tools for machine learning. Weights & Biases is a series C company with $250 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.
We're hiring a Korean-speaking Machine Learning Engineer - Customer Success to help our customers solve difficult, real-world problems and engage in ground-breaking research by using our developer tools in their machine learning pipelines. 
In this role, you'll be working with the most sophisticated ML teams in the world working on some of the toughest ML problems in computer vision, robotics, natural language processing, and more. Your responsibility will be to make their work easier with our tools. You'll have the opportunity to work with ML teams across multiple industries to uncover their ML needs, improve their ML workflow, explore how W&B fits into their environment, collaborate on projects, and educate them on the best practices of our product.
Machine Learning Engineers on our customer success teams are critical to the success of our customers at Weights & Biases. You'll partner with Customer Success, Support, Product and Engineering teams to own the technical onboarding and success of our customers, serving as the primary knowledge owner and face to our customers. You'll help drive adoption, understand innovative customer use cases, and serve as the primary problem solver in our customers' machine learning workflows.
This is a perfect opportunity for anyone who has machine learning experience, is customer-oriented, and is looking to work with the top ML companies in the world.

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

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

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

Our 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


We encourage you to apply even if your experience doesn't perfectly align with the job description as we seek out diverse and creative perspectives. Team members who love to learn and collaborate in an inclusive environment will flourish with us. We are an equal opportunity employer and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need additional accommodations to feel comfortable during your interview process, reach out at careers@wandb.com.
#LI-Remote
Apply now Apply later
  • Share this job via
  • or

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: AWS Azure Computer Vision Deep Learning Docker Engineering fastai GCP HuggingFace Keras Kubernetes LightGBM Linux Machine Learning MLOps NLP OpenAI Pipelines Python PyTorch Research Robotics Salesforce Scikit-learn TensorFlow Travel Weights & Biases XGBoost

Perks/benefits: Career development Competitive pay Equity Flex hours Flex vacation Gear Health care Medical leave Parental leave Startup environment Travel

Regions: Remote/Anywhere Asia/Pacific
Country: Japan
Job stats:  66  2  1

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.