Machine Learning Engineer - Customer Success
At Weights & Biases our mission is to build the best tools for machine learning.
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 WB in solving their problem
- Provide customer training sessions, product demos, and workshops covering best practices different solutions WB 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
- 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
Who this role is for
- Passion for machine learning: You understand how exciting the ML space is and how quickly it's growing. You're excited to speak with industry leaders at the forefront of ML research and development
- Outgoing and friendly: You'll love this role if you enjoy connecting with real users every day, helping them adopt the Weights Biases platform, and answering all of their questions
- Technically Savvy: You enjoy instrumenting models in PyTorch, Keras, and TensorFlow and understand complicated workflows
- Autonomous and adaptable: You understand different companies have different workflows, and you're excited to solve these challenges
- Curious and Driven: You want to understand future customers' ML workflow and prove how Weights Biases will improve their day-to-day
Why join us?
- Top-tier machine learning teams rely on our tools for their daily work at companies including OpenAI, Toyota Research Institute, Lyft, Samsung, and Pandora.
- You'll never stop learning. This role gives you first-hand experience talking with leading researchers in the field, understanding their problems, and directly shaping the product direction.
- Our experienced founding team has successfully built and sold ML tools in the past at Figure Eight, and their deep knowledge of our industry, empathy for our users, and skillful management is driving WB to success.
- Customers genuinely benefit from our tool. Here's a quote from Wojciech Zaremba, Cofounder and Robotics Lead, OpenAI: "WB allows to scale up insights from a single researcher to the entire team, and from a single machine to hundreds of them."
- A best-in-class product in one of the fastest-growing and largest market segments
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
About this role
March 26th, 2023
January 26th, 2023
Full Time
Apply now
Job expired?Please let Weights & Biases know you found this job on Himalayas. This will help us grow!
About Weights & Biases
Learn about Weights & Biases and their company culture.
We're building a culture where people love coming to work to build cool things and collaborate with other smart people. It’s important to us that everyone feels comfortable being themselves and being honest with each other, and all of us take responsibility for making our customers successful. We love to work with people who are driven, kind and proactive. We care about diversity and if you are part of an underrepresented minority, we especially encourage you to apply to work here.
We are contributing to responsible AI with tools for transparency and reproducibility in model development and deployment.
Benefits
As second time founders, our company is small but well funded by top tier investors. We offer market salary, benefits and equity comparable to a Series C startup. When we're not all working from home, our sunny, pet-friendly office is located in the SOMA district of San Francisco.
Tech stack
Learn about the technology and tools that Weights & Biases uses.
Benefits and perks
Learn about the benefits and perks that Weights & Biases provides.
Company retreats
We work hard to make time to be together for Department and Company offsite. Our goal is to make time to be together and bond so we can be confident in our asynchronous work when we're apart!
Healthcare benefits
🩺 100% Medical, Dental, and Vision for employees and Family Coverage.
Retirement benefits
🏦 401(k) to set you up for a future in saving for yourself.
Home office budget
$500 to set yourself up for work from any home office.
Apply now
Job expired?Please let Weights & Biases know you found this job on Himalayas. This will help us grow!
About this role
March 26th, 2023
January 26th, 2023
Full Time
