3 months ago
Base Salary
$150k - $227k/yr
Responsibilities
- Build end-to-end data integrations that synchronize customer data with Scale’s platform.
- Work with customer engineering teams to optimize data pipelines, API endpoint designs, and input/output schemas.
- Design and maintain playbooks, internal tools, documentation, and SDKs for long-term customer success.
- Partner with Engineering and Operations to resolve technical blockers, debug delivery issues, and own customer technical escalations.
- Own the customer’s technical experience throughout their engagement with Scale.
- Collaborate with Account Executives and Product Managers to identify customer-specific feature requests.
- Develop expertise in large language models, 2D image annotation, and API integrations.
- Represent Scale and engage with customers at major events.
Requirements
- An active TS/SCI clearance is required.
- Experience as a customer-facing engineer or in a similar hybrid role is required.
- Hands-on technical client experience in a pre- or post-sales capacity is required.
- Development experience with Python, JavaScript, or other modern programming languages is required.
- A strong engineering background is expected, ideally in computer science, mathematics, or another quantitative field.
- Strong project management, interpersonal, presentation, and cross-team communication skills are required.
- Experience with AI, classified environments, or technical go-to-market work is preferred.
- Understanding of DevSecOps principles and experience with Kubernetes, Helm charts, Ansible, or similar infrastructure automation tools are preferred.
Benefits
- Comprehensive health, dental, and vision coverage
- Retirement benefits
- Learning and development stipend
- Generous paid time off
- Potential commuter stipend
- Full-time position with location-specific salary ranges for Washington DC/Hawaii and St. Louis/Suffolk
Tech Stack
Categories
Forward DeployedSolutions Engineering
About Scale AI
Scale AI builds data annotation services and AI development tools for enterprises and government agencies, sold as a platform and managed services. Its products include the Scale Generative AI Platform for building and evaluating agents and the Data Engine for collecting, curating, and labeling training data, including RLHF and model evaluation. Founded in 2016 and headquartered in San Francisco, the company is privately held and works across domains from computer vision to LLM applications.