Senior Software Engineer, GenAI Safety & Evaluation

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Senior Software Engineer, GenAI Safety & Evaluation

About the Job

In today's tech-driven world, AI is revolutionizing software. AI exponentially enhances human intelligence, prompting top tech firms to develop large-scale LLMs and enterprises to integrate AI into their products. To ensure the safety, alignment, and usefulness of these models, high-quality human-generated data and evaluation are crucial. Since ChatGPT's launch, Scale has been a leader in providing post-training, fine-tuning, and human preference alignment (RLHF) data through our Generative AI Data Engine, shaping the future of human-AI interaction.

As customers continually refine their models, trustworthy performance evaluations and identification of weaknesses become critical. Scale’s human experts conduct these evaluations, guiding model developers on optimizing their technical investments.

The GenAI Safety & Evaluation team at Scale creates a top-tier customer-facing model evaluation platform. This platform simplifies the launch of new evaluation workflows, provides detailed insights into test case-level results, and influences model development roadmaps. By joining our team, you will shape industry-standard evaluation practices, impacting billions worldwide. You’ll also build impactful solutions from the ground up as part of our innovative product team.

Collaborating with Scale’s Safety, Evaluations, and Alignment Lab (SEAL) and expert red team, you will drive AI safety through rigorous model testing endorsed by leading institutions.

Key Responsibilities

  • Deliver customer-ready features exhibiting engineering excellence.
  • Work with backend, frontend, and ML model interactions.
  • Oversee the entire product lifecycle—from idea to production.
  • Adapt to new technologies swiftly, multitask, and learn quickly.
  • Collaborate with cross-functional teams to define, design, and launch new product features and experiences.
  • Execute fast-turnaround product requests for high-value customers.

Preferred Qualifications

  • 5+ years of engineering experience post-graduation.
  • Proficiency in Python, Node, React, Next.js, and MongoDB.
  • Strong knowledge of algorithms, data structures, and object-oriented programming.
  • Experience in scaling products at hyper-growth startups.
  • Enthusiasm for AI technologies.
  • Strong communication skills to thrive in a writing-first culture.
  • Excellent problem-solving skills and a team-oriented mindset.

Additional valuable skills include:

  • Proficiency in software engineering best practices.
  • Experience with AI platforms, generative models, and LLMs.
  • Expertise in building ML infrastructure and AI-powered solutions.
  • Experience launching new products from concept to reality.

Compensation and Benefits

Scale offers competitive compensation packages, including base salary, equity, and comprehensive benefits. Salary ranges depend on work location and other job-related factors. Our benefits package includes comprehensive health, dental, and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. This role may also qualify for additional benefits such as a commuter stipend.

Pay transparency details for full-time positions in San Francisco, New York, and Seattle:

Salary Range: $160,000—$225,000 USD

About Us

At Scale, we drive AI innovation across industries, facilitating the transition from traditional software to AI. Our mission is to accelerate AI adoption, and our products support cutting-edge LLMs, generative models, and computer vision technologies. We are trusted by renowned entities such as OpenAI, Meta, Microsoft, U.S. Army, and GM.

We champion diversity and inclusivity, providing equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status.

We offer reasonable accommodations for applicants with physical and mental disabilities. For assistance, contact . Learn more from the U.S. Department of Labor's .

For more details on data privacy, please refer to our internal policies designed to protect personal data.
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