Solutions Engineer

Labelbox’s mission is to build the best products for humans to advance artificial intelligence. Real breakthroughs in AI are reliant on the quality of the training data. Our training data platform enables organizations to improve their machine learning models far quicker and more accurately. We are determined to build software that is more open, easier-to-use, and singularly focused on getting our customers to performant ML faster.

Current Labelbox customers are transforming industries within insurance, retail, manufacturing/robotics, healthcare, and beyond. Our platform is used by Fortune 500 enterprises including Allstate, Black + Decker, Bayer, Warner Brothers and leading AI-focused companies including FLIR Systems and Caption Health. We are backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures (Google's AI-focused fund), Databricks Ventures, Snowpoint Ventures and Kleiner Perkins.

As a Solutions Engineer you are in the unique position of helping Labelbox customers build and operationalize transformational AI. You will partner with Account Executives to discover customer’s technology needs for ML Model Development. As the technical expert on the team, you’ll guide customers through demos and POCs that prove the value of Labelbox, identifying solutions to any technical obstacles. You will be a liaison between engineers, data scientists and product managers, paving a successful customer journey through the sale.

What you’ll do

• Partner with account executives consulting customers in a technical pre-sales capacity
• Be current with the emerging state of the ML dev lifecycle where training data is the source code
• Understand & qualify customer goals, articulating Labelbox’s ability to meet them
• Demonstrate value of Labelbox through customer demos Drive successful customer POCs managing the plan, success criteria and execution
• Guide customers through architecture designs identifying solutions for various environments including on prem, SaaS/PaaS integration, API, SSO, federated access and security
• Be a liaison between product and customers, aligning features with customer value
• Continuously learn and improve skills in software, computer vision, and ML
• Develop external content including docs, code recipes, blog posts and case studies
• Assist with customer RFPs and security reviews

What you’ll need to succeed

• Passionate about solving customer problems
• 2+ years of experience in a sales/solutions engineering, solutions architecture or technical consulting role, ideally in the ML or B2B SaaS space
• Hands on experience in several of the following areas: Distributed systems integration with REST APIs, webhooks, JSON & XMLStrong scripting proficiency in one or more of the following: Python (preferred), Javascript, Node.Js, C#, Java, or other scripting languages.
• Data analytics, machine learning, computer vision, data pipelines, data engineering, data operations, ETL concepts and workflow
• SDLC & ML Lifecycle. DevOps including CI/CD and TDD
• Deep Learning frameworks like TensorFlow and PyTorch
• Ability to travel 10% to 25%
• Strong communication and presentation skills. Comfort with technical decision makers (engineer, architect, data scientist) or C level executives
• Excellent organizational skills working with multiple customers simultaneously while prioritizing competing demands
• Bachelors in CS, engineering, mathematics or equivalent experience
• High energy, self-starter comfortable with ambiguity in entrepreneurial environments