About the job

About the Role

We are hiring for a client building the next generation of data annotation infrastructure to serve enterprise AI companies. We need an experienced Solutions Engineer who has worked directly with clients at a major data labeling company and can help us establish both our technical foundation and market credibility.

You’ll be a founding team member responsible for designing client solutions, building our core platform capabilities, and serving as our technical face to enterprise prospects. Your experience will be crucial for both product development and business development.

Key Responsibilities

Client Solutions & Technical Sales (50%)

• Work directly with prospective clients to understand their annotation requirements and use cases
• Design and demo custom annotation workflows for enterprise prospects
• Build proof-of-concept projects and pilot implementations for key clients
• Serve as technical credibility in sales conversations and client meetings
• Translate client needs into platform requirements and technical specifications

Platform Development (50%)

• Build core annotation workflows, interfaces, and quality control systems
• Develop client-specific integrations with ML frameworks (PyTorch, HuggingFace, TensorFlow)
• Create demo environments and showcase implementations for different use cases
• Design APIs and integration patterns that enterprise clients can easily adopt
• Implement quality assurance processes and validation systems for annotation projects

Requirements

Experience

• 3-6 years in client-facing technical roles at data labeling or ML infrastructure companies
• Direct experience at Scale AI, Surge AI, Appen, Labelbox, or similar working with enterprise clients
• Proven track record of implementing annotation solutions for real client projects
• Understanding of enterprise ML workflows and how labeled data integrates into model training

Technical Skills

• Python proficiency with data processing libraries (pandas, PyTorch, spaCy, HuggingFace)
• API integration experience with ML platforms and cloud services (AWS, GCP)
• Annotation tools expertise – Label Studio, Prodigy, custom interfaces, or similar platforms
• Data pipeline knowledge – handling large datasets, quality control, and validation workflows
• Basic frontend skills – ability to build demos and simple interfaces (React/JavaScript preferred)

Client & Communication Skills

• Enterprise client experience – worked with Fortune 500 or major AI companies
• Technical presentation skills – can explain complex annotation concepts to business stakeholders
• Requirements gathering – skilled at understanding and documenting client needs
• Project management – experience delivering annotation projects on time and within scope

Domain Knowledge

• RLHF and LLM training workflows – preference data, instruction tuning, alignment processes
• Computer vision annotation – bounding boxes, segmentation, object detection, video annotation
• NLP annotation tasks – text classification, NER, sentiment analysis, conversation evaluation
• Quality metrics – inter-annotator agreement, statistical validation, bias detection
• Enterprise requirements – security, compliance, audit trails, and scalability considerations

Nice to Have

• Recent experience at Scale AI or Surge AI working with their largest enterprise clients
• Industry expertise in healthcare, autonomous vehicles, finance, or legal tech annotation
• Sales or business development background with technical products
• Open source contributions to annotation tools or ML infrastructure projects
• Conference speaking or thought leadership in the annotation/AI space
• Startup experience – comfortable in fast-moving, ambiguous environments