Deep Research Agent Tech Lead

<p><strong>Scale AI</strong> is seeking a highly technical and strategic <strong>Staff / Senior Staff Machine Learning Engineer</strong> to act as the <strong>Tech Lead (TL)</strong> for our next generation of deep research agents for the Enterprise. This high-impact role will drive the technical direction and oversight for <strong>Deep Research Agent Development</strong>, translating cutting-edge research in <strong>Generative AI, Large Language Models (LLMs),</strong> and <strong>Agentic Frameworks</strong> into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency.</p> <p>The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus.</p> <h3><strong>Responsibilities</strong></h3> <h4><strong>Technical Leadership &amp; Vision</strong></h4> <ul> <li><strong>Set the Technical Roadmap:</strong> Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals.</li> <li><strong>Drive Breakthrough Research to Production:</strong> Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on <strong>integrating diverse data modalities</strong>.</li> <li><strong>Core Agent Capabilities Development:</strong></li> <ul> <li><strong>Advanced Knowledge Retrieval: </strong>Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises.</li> <li><strong>Data analysis:</strong> Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas.</li> <li><strong>Multimodal Intelligence:</strong> Lead the integration of <strong>Multimodal AI</strong> capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent's knowledge base.</li> </ul> <li><strong>Architecture &amp; Design:</strong> Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.</li> <li><strong>Technical Excellence:</strong> Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems.</li> </ul> <h4><strong>Team Leadership &amp; Mentorship</strong></h4> <ul> <li><strong>Lead and Mentor:</strong> Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth.</li> <li><strong>Recruiting &amp; Growth:</strong> Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team.</li> <li><strong>Cross-Functional Influence:</strong> Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent solutions.</li> </ul> <h3><strong>Basic Qualifications</strong></h3> <ul> <li>Bachelor's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.</li> <li>8+ years of experience in software development, with at least 6 years focused on <strong>Machine Learning, Deep Learning, or Applied Research</strong> in a production environment.</li> <li>2+ years of experience in a formal or informal <strong>Technical Leadership</strong> role ( ... (truncated, view full listing at source)