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

Job description
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 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. This specific role will be focusing more on W&B’s engagement with Prospective customers who are evaluating W&B for their use case. 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. Specifically, the person in this role will be responsible for assessing the prospective customer’s technical requirement and specification, demonstrate W&B functionality that highlights those capabilities, designing and executing proof of values (as needed) and securing a technical success in the evaluation process.

Machine Learning Engineers on our customer success teams are critical to the success of our customers at Weights & Biases. You'll partner with Sales, Support, Product and Engineering teams to own the technical success of the pre-sales evaluation of W&B for our prospective customers, serving as the primary knowledge owner and face to our customers.

This is a perfect opportunity for anyone with 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
• 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

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

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