Customer Support Engineer, Machine Learning - LATAM (Remote)
Buenos Aires
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Weights & Biases
Weights & Biases, developer tools for machine learningWeights & Biases is a Series C company with $250M in funding and over 200 employees. We proudly serve over 1,000 customers and more than 30 foundation model builders including customers such as OpenAI, NVIDIA, Microsoft, and Toyota.
Support is a deep part of our culture here at Weights & Biases. We believe that the best way to build a great product is to listen to real users and follow their lead to shape our priorities and roadmap. In this role, you will work on a diverse set of problems in a fast-moving environment, collaborate cross-functionally with our team to support our users and help shape our product.
Your main goal will be to quickly get answers to all user messages. Customers write in with highly technical questions, suggestions, or bug reports, and we need to give them timely responses to fulfill SLAs. In this role, you will act as the face of the company and the first line of support in North American Time Zones. Ideally, we're looking for someone with technical skills who would like to support our customer base. If you've found yourself wanting to be more external but still build programming/machine learning skills, this is the role for you.
Responsibilities:
- Quickly respond to all inbound support requests including email, live chat and community forums
- Triage bugs and requests based on customer type and severity of issue
- Track inbound and outbound responses to ensure contact SLAs are being met
- Maintain a fast response time for entire user base
- Collaborate with the engineering and product team when troubleshooting issues and providing feedback on features
- Recognize trends in user messages to help identify areas of improvement in internal or external documentation
- Learn W&B product features and build up knowledge base to resolve issues on your own
Requirements:
- Must be based in Argentina or Uruguay, with a preference for candidates in Buenos Aires or Montevideo
- Fluent in English, both written and spoken, in order to communicate with our global team and stakeholders
- 2+ Programming experience, from either an engineering role, a computer science degree, or personal projects
- Python expert
- Experience using any of the following: Keras, Tensorborad, Tensorflow, Pytorch, Pytorch Lightning, Jupyter notebooks, colabs, matplotlib and other ML frameworks and tools
- A passion for connecting with real users and enabling them to be power users of the product
- Good organization of assigned requests to oversee timely follow-up for every message
- Work autonomously in a self-directed environment
- Proactively find ways to improve processes and collaborate internally
- Answer messages with a kind, thoughtful tone that makes users feel appreciated and connected to our team
- Interest in machine learning
Strong Plus:
- Have worked in a small-stage startup previously
- Previous experience in machine learning
- Customer service experience in a technical SaaS environment
- Experience in frontend frameworks
- Experience with Docker, AWS, GCP, Azure
- Experience with Kubernetes or other cloud infrastructures
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
#LI-Remote
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Azure Computer Science Deep Learning Docker Engineering GCP Generative AI Jupyter Keras Kubernetes Machine Learning Matplotlib OpenAI Python PyTorch TensorFlow Weights & Biases
Perks/benefits: Career development Competitive pay Equity / stock options Flex vacation Gear Health care Home office stipend Medical leave Parental leave Startup environment
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