Machine Learning Research Engineer, GenAI Applied ML

<h1>About This Role</h1> <p>Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviors, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes.</p> <p>Ideal for exceptional engineers with deep research rigor and a relentless focus on practical, high-impact systems. You will iterate rapidly with data, leverage AI tools to accelerate development, and collaborate tightly across engineering, product, and research.</p> <p>If you excel at turning frontier agent research into reliable deployed systems, we want to hear from you.</p> <p><strong>You will:</strong></p> <ul> <li>Build and deploy multi-agent systems for agentic reasoning validation</li> <li>Develop pipelines to detect errors and scale human judgment</li> <li>Combine classical ML, LLMs, and multi-agent techniques for reliability</li> <li>Lead research into agent failure modes and ship fixes</li> <li>Use AI tools to speed prototyping and iteration</li> <li>Build data-driven evaluations and deploy rapid improvements</li> <li>Integrate systems into Scale's platform</li> </ul> <p><strong>Ideally You’ll Have:&nbsp;</strong></p> <ul> <li>PhD or MSc in Computer Science, Mathematics, Statistics, or related field</li> <li>3+ years shipping scaled production ML systems</li> <li>Demonstrated real-world impact</li> <li>Mastery of PyTorch, TensorFlow, JAX, or scikit-learn</li> <li>Deep expertise in agentic LLMs and multi-agent systems</li> <li>Strong software engineering and microservices (AWS/GCP)</li> <li>Rapid, data-driven iteration</li> <li>Proficiency using AI tools to accelerate work</li> <li>Strong research depth with practical bias</li> <li>Excellent cross-functional communication</li> </ul> <p><strong>Nice to Have:&nbsp;</strong></p> <ul> <li>Experience prototyping agent ev