Senior Software Engineer, GenAI - Scale AI : Job Details

At Scale AI, our mission is to accelerate the development of AI applications. Scale has been a leading AI data foundry for 8 years, supporting advancements in generative AI, defense applications, and autonomous vehicles. We are accelerating the abundance of frontier data to advance Artificial General Intelligence (AGI) and deepen our capabilities for enterprise and government evaluations.

About Data Engine

Our Generative AI Data Engine powers the world's most advanced LLMs and generative models through RLHF, human data generation, model evaluation, safety, and alignment. The data we produce supports critical AI developments and interactions across industries.

Our Approach

As part of the interview process, opportunities may be available across several teams within the GenAI Engineering organization based on interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. These teams drive Scale's AI data operations—from building high-impact datasets that push LLM capabilities, to onboarding and incentives, to safeguarding data integrity through trust, safety, and security measures.

• Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers
• Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal
• Collaborate closely with internal operators to identify bottlenecks and ship fast, pragmatic solutions
• Own core systems critical to our contributor platform, with direct impact on Scale's GenAI data pipeline and business outcomes
• Architect and scale infrastructure capable of handling millions of tasks per week with high reliability and low latency
• Partner cross-functionally with ML teams, Forward Deployed Engineers, and Product to ensure data quality and operational excellence
• Contribute to a strong engineering culture through mentorship, code reviews, and process improvements

• 5+ years of software engineering experience, ideally in high-growth, product-focused environments
• Proven track record of shipping production systems at scale
• Drive reliability and performance across critical infrastructure systems to scale predictably with high availability
• Strong technical depth in front-end frameworks, distributed systems, data infrastructure, or developer tooling
• Experience across the stack, ideally with React, TypeScript, Node.js, Python, MongoDB, Elasticsearch, and/or Temporal
• Strong product sense and ability to translate ambiguous problems into technical solutions
• Comfortable in a fast-paced, high-ownership environment with a bias toward execution
• Hybrid role based in San Francisco or New York City

Compensation and benefits details are provided during the hiring process. The base salary range for this full-time position in San Francisco, New York, and Seattle is $188,000 – $235,000 USD. Eligible roles may include equity-based compensation and comprehensive benefits such as health, dental, and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Some roles may also offer additional benefits such as a commuter stipend.

Please reference the job posting subtitle for the location. This role supports a hybrid arrangement in San Francisco or New York City.

At Scale, we enable the transition from traditional software to AI by powering the world's most advanced LLMs, generative models, and computer vision models. We are trusted by leading AI companies, government agencies, and enterprises, and we're expanding our team to accelerate AI development.

We are committed to an inclusive and equal opportunity workplace. We do not discriminate on the basis of race, color, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity, or Veteran status. We provide reasonable accommodations in the application process for applicants with disabilities. For more information about our privacy practices, please refer to our privacy policy.