Staff Research Engineer - Post Training

As a Staff Research Engineer at P-1 AI, you will be responsible for building and deploying AI systems with advanced multimodal large language models. Your role includes writing robust machine learning code, developing algorithms, conducting data evaluations, and collaborating with domain experts to tackle significant real-world challenges in engineering.

To be considered for the Staff Research Engineer position at P-1 AI, candidates should possess strong programming skills, a deep understanding of machine learning, and experience with large distributed systems. A background in fields such as statistical machine learning, physics, or mathematics is highly desirable, along with experience working with LLMs and conducting autonomous experiments.

Essential technical skills for the Staff Research Engineer role at P-1 AI include proficiency in Python and C++, a solid grasp of machine learning principles, and experience with PyTorch and LLM post-training techniques. A deep understanding of LLM architectures and the ability to debug complex ML codebases are also critical for success in this role.

The interview process for the Staff Research Engineer position at P-1 AI involves several stages, including an initial screen with the Head of Talent, followed by interviews with the Head of AI and two technical interviews focusing on software engineering and ML debugging. The process concludes with a final interview with the CEO, providing a comprehensive evaluation of your fit for the role.

At P-1 AI, our culture thrives on innovation, intellectual curiosity, and collaboration. As a Staff Research Engineer, you will work in a dynamic startup environment that encourages exploration and rapid learning, where your ideas are valued, and problem-solving is a collective effort.

In this response, you should discuss specific projects where you worked with large distributed systems, detailing the challenges you faced, the solutions you implemented, and how these experiences relate to the Staff Research Engineer role. Highlight any tools or technologies you utilized and the outcomes of your work.

Here, provide examples of machine learning algorithms you have used in previous projects. Explain their relevance to the problems they addressed, demonstrating your coursework or hands-on experience, and how these experiences equip you for the Staff Research Engineer position.

Share your systematic approach to debugging, including methods such as code reviews, using debuggers, logging, and performance tracking. Explain how you would apply these techniques as a Staff Research Engineer at P-1 AI to maintain and enhance code quality.

In your answer, provide a high-level overview of the LLM architectures you have experience with. Discuss their components—like layers, attention mechanisms, and any modifications you implemented to optimize their performance, and how these are applicable to the work at P-1 AI.

Narrate a specific instance where you encountered a significant challenge in a machine learning project. Detail the steps you took to resolve the issue and the lessons learned. This will help demonstrate your problem-solving skills as a Staff Research Engineer.

Identify trending topics in LLM research that resonate with you. Discuss why these advancements fascinate you and how they could impact the future of AI, particularly in the context of the work at P-1 AI.

Explain your strategies for continuous learning, such as following leading research papers, participating in relevant conferences, or engaging with open-source projects. Relate this to your approach as a Staff Research Engineer at P-1 AI.

Outline your experimental design process, from hypothesis formulation to results analysis. Include details on how you document and interpret your findings, as well as any tools or methodologies you use that are relevant to the Staff Research Engineer role.

In your response, highlight your experience working within multidisciplinary teams. Discuss how you communicate technical concepts to non-technical stakeholders and your strategies for fostering collaboration across different fields as a Staff Research Engineer.

Reflect on your personal motivations for thriving in dynamic settings. Share why you prefer startups, such as the opportunity for rapid learning, innovation, and impact, and how these align with P-1 AI’s mission and culture.