I've searched for AI Research Scientist roles with a focus on generative models in New York, requiring at least 3 years of experience in deep learning and offering full-time positions with competitive benefits. I found 45 positions that match your criteria.

Sure. Here's the analysis:

Job Analysis:

The AI Research Scientist specializing in generative models at Radical AI is fundamentally tasked with pioneering new methodologies in materials discovery through advanced artificial intelligence techniques. This role is critical as it aims to transform and expedite traditional R&D processes, a significant challenge in materials science. Responsibilities include designing large-scale experiments, collaborating across various teams (such as quantum chemistry and engineering), and transitioning research models into production. This requires a seamless integration of AI theory and practical application, representing the convergence of multiple disciplines. Success in this role is measured not just by individual performance but also by the ability to contribute to team goals and the broader research community, especially through publications in top-tier venues that shape the future of both AI and materials science. Given the innovative pace of Radical AI, candidates will encounter problems that require creative, unconventional solutions, thus prior experience overcoming similar challenges, especially in high-stakes environments, will be vital.

Company Analysis:

Radical AI operates at the forefront of materials research and development by integrating AI into traditionally slow scientific processes. Its mission reflects a commitment to addressing substantial global challenges, positioning the company as a disruptor rather than a conventional player in the sector. This suggests a dynamic, fast-paced work environment that values innovation and creative thinking. Company culture likely emphasizes collaboration, as indicated by the cross-functional nature of the role, making interpersonal skills and teamwork essential. The organizational context would place the AI Research Scientist as a key player among various technical teams, likely providing visibility to senior leadership through collaborative projects and impactful research contributions. The strategic alignment of this role is crucial as it embodies the company’s growth-focused vision—developing cutting-edge AI models that can lead to breakthroughs in materials science, a field critical for many advancing industries. Candidates must resonate with this mission and be prepared to not only contribute to research but also partake in shaping the workplace culture of innovation and excellence.

Absolutely. Here are some mock interview questions that could come up:

• Tell me about a time when you faced a significant challenge in transitioning AI research into a production environment. How did you approach it?
• Can you describe your experience with conducting large-scale experiments in generative modeling? What factors did you consider?
• How do you handle team disagreements when working on a complex project? Can you give an example?
• Describe a project where you used generative models to solve a scientific problem. What was your reasoning behind the chosen approach?
• How would you approach developing benchmarks to validate generative models in materials discovery?
• Can you explain how you would leverage flow matching or diffusion models in your research for materials science?
• Imagine you are tasked with mentoring a junior team member who is struggling with a research concept. How would you guide them?
• If faced with ambiguous results from an experiment, what steps would you take to determine the next course of action?
• What attracts you to the mission of Radical AI and how do you see your skills contributing to it?
• In your view, what are the future trends in AI and materials science that companies like Radical AI should focus on?
• What was the most impactful paper or project you've authored, and how did it influence the field or your perspective?
• How would you assess the impact of your team's experiments on the broader goals of the company?
• What questions do you have about Radical AI's approach to integrating AI with traditional materials science processes?
• How do you see your experience aligning with the unique challenges faced by Radical AI in pioneering generative materials science?