Applied AI Researcher, System Self-Construction

Distyl Inc.

Job Overview

Location

Indiana, USA

Job Type

Full-time

Full Job Description

📋 Description

• Distyl AI is at the forefront of revolutionizing enterprise operations by developing production-grade AI systems for Fortune 500 companies. Through a strategic partnership with OpenAI, proprietary software accelerators, and deep enterprise AI expertise, we deliver tangible AI solutions with remarkable speed, often within a single quarter. Our impact spans diverse industries, including insurance, consumer packaged goods, and non-profits, empowering clients to identify, build, and realize value from their Generative AI investments, frequently for the first time.
• As an Applied AI Researcher specializing in System Self-Construction, you will be instrumental in building systems that possess the capability to construct other systems. This pivotal role involves designing advanced architectures that can autonomously generate, assemble, and refine sophisticated sub-systems. You will delve into the intricacies of meta-learning loops, automated pipeline generation, and self-architecting frameworks, aiming to significantly reduce the human bottleneck inherent in complex system creation.
• Your research will focus on recursive design principles, exploring how systems can represent, evaluate, and evolve their own construction processes. This cutting-edge work draws inspiration from meta-learning, program synthesis, and evolutionary computation, pushing the boundaries of what it means for a system to truly 'understand' and redesign itself. You will be defining the frontier of self-referential, generative system architectures, contributing to a paradigm shift in how AI systems are conceived and built.
• This role demands a creative and forward-thinking researcher who is not content with incremental improvements on benchmarks or optimizing existing processes. Instead, we seek individuals driven to creatively redefine the very nature of software utilization. While drawing from diverse academic backgrounds, you will possess a strong research track record, operate with an AI-native mindset, and thrive in an environment that encourages innovation beyond traditional research paradigms.
• Key responsibilities include architecting and developing systems capable of dynamic component interaction, drawing parallels to graph-based planners, agent orchestration frameworks, workflow engines, or automated pipeline builders. You will be focused on building intelligent systems *using* existing models rather than solely focusing on training or fine-tuning new ones. This involves deep expertise in compound AI systems, agentic collaboration, and advanced techniques such as ensembling, ReAct, and Graph-of-Thoughts.
• You will be expected to demonstrate a proven track record of research achievements, whether evidenced through publications in top-tier journals, impactful contributions shared on platforms like Twitter, or other demonstrable outputs. A fundamental aspect of this role is the daily, practical application of AI tools. You should be adept at leveraging tools like ChatGPT, Cursor, and Perplexity to accelerate your own research and development workflows, embodying the AI-native approach we champion.
• Strong programming and data analysis skills are essential. While not necessarily a traditional software engineer, you must be capable of prototyping your innovative ideas and conducting rigorous experiments to validate their effectiveness for our Fortune 500 clients' Heads of AI. A bias towards 'showing' rather than 'telling' is critical; our clients value demonstrable AI power today over abstract, long-term theoretical concepts.
• You will contribute to a mission-driven, fast-paced culture that highly values curiosity, pragmatism, and excellence. This is an opportunity to work on high-impact projects with leading enterprises, gain access to state-of-the-art AI models, and utilize generous allowances for modern AI tools. The work you do will directly influence the future of enterprise AI and the operational efficiency of global organizations.
• The System Self-Construction team is at the heart of Distyl's innovation, tackling some of the most challenging problems in AI system design. Your work will directly contribute to the company's mission of delivering rapid, impactful AI solutions to our enterprise clients, solidifying Distyl's position as a leader in the production-grade AI space.
• This role offers a unique opportunity to shape the future of AI development by creating systems that can build and improve themselves, leading to unprecedented levels of automation and efficiency in complex software creation. You will be part of a collaborative and intellectually stimulating environment where groundbreaking ideas are encouraged and brought to life.

🎯 Requirements

• Proven experience in building modular and composable systems, such as graph-based planners, agent orchestration frameworks, workflow engines, or automated pipeline builders.
• Expertise in building intelligent systems using existing AI models, focusing on compound AI systems, agentic collaboration, and techniques like ensembling, ReAct, or Graph-of-Thoughts.
• A strong, demonstrable track record of research results, evidenced through publications, public contributions, or other significant outputs.
• Daily, practical usage of AI tools (e.g., ChatGPT, Cursor, Perplexity) to enhance personal workflow and productivity.
• Strong programming and data analysis skills sufficient for prototyping and experimental validation.

🏖️ Benefits

• Meaningful equity in a rapidly growing AI company.
• Comprehensive benefits package, including 100% covered medical, dental, and vision for employees and dependents.
• 401(k) with additional perks, such as commuter benefits and in-office lunch.
• Access to state-of-the-art AI models and generous usage of modern AI tools.
• Ownership of high-impact projects across top-tier enterprises.

Skills & Technologies

React

Rails

GitHub

Remote

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Distyl Inc.

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About Distyl Inc.

Distyl is a cloud-native platform designed to simplify and accelerate the development and deployment of machine learning (ML) models. It provides a unified environment for data preparation, model training, versioning, and deployment, enabling data scientists and ML engineers to move from experimentation to production faster. The platform offers features such as automated data pipelines, managed training infrastructure, and scalable model serving. Distyl aims to reduce the complexity and operational overhead associated with MLOps, allowing organizations to focus on building and deploying impactful ML solutions. It supports various ML frameworks and integrates with existing cloud infrastructure.

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