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Machine Learning Research Engineer - Generative AI Applied ML

Scale AISan Francisco, CA; New York, NY
On-site Full-time $176K/yr - $220K/yr

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Responsibilities Design and implement multi-agent systems for the validation of agentic reasoning. Develop robust pipelines for error detection and enhancement of human judgment. Integrate classical ML techniques, LLMs, and multi-agent methodologies to improve reliability. Lead investigations into agent failure modes and deliver effective solutions. Utilize AI tools to facilitate rapid prototyping and iteration. Conduct data-driven evaluations and implement swift improvements. Seamlessly integrate systems into Scale's platform. Preferred Qualifications PhD or MSc in Computer Science, Mathematics, Statistics, or a related field. 3+ years of experience in deploying scalable production ML systems. Proven track record of generating real-world impact. Expertise in PyTorch, TensorFlow, JAX, or scikit-learn. In-depth knowledge of agentic LLMs and multi-agent systems. Strong software engineering skills and experience with microservices architecture (AWS/GCP). Ability to iterate quickly and data-driven. Familiarity with AI tools to enhance productivity. Strong research background with a practical approach. Excellent communication skills for cross-functional collaboration. Nice to Have Experience in prototyping agent evaluation/reliability systems. Involvement in human-in-the-loop or annotation pipeline projects. Contributions to open-source projects related to agents, evaluation, or alignment. Publications on agent reliability in conferences such as NeurIPS, ICML, or ICLR.

About the job

About This Role

Join Scale AI's Applied ML team as a Machine Learning Research Engineer, focusing on the development of advanced data infrastructure for leading agentic large language models (LLMs) such as ChatGPT, Gemini, and Llama. You will be responsible for architecting scalable multi-agent systems aimed at validating agentic reasoning and behaviors, enhancing human expertise, and conducting research to address real-world agent reliability failures, even in the face of strong benchmarks. Your contributions will directly impact the deployment of production fixes.

This role is ideal for exceptional engineers who possess a deep research rigor and a strong commitment to creating practical, high-impact systems. You will iterate rapidly using data, leverage AI tools for accelerated development, and collaborate closely with engineering, product, and research teams.

If you have a knack for transforming cutting-edge agent research into dependable deployed systems, we would love to hear from you.

About Scale AI

Scale AI is a leading company in artificial intelligence, specializing in creating data infrastructure that powers AI applications. Our team focuses on innovative approaches to enhance AI capabilities and reliability, making significant contributions to the field of machine learning and data science.

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