Join Distyl AI as an Applied AI Researcher to innovate self-constructing systems in a hybrid work environment.
Posted by employer 1 year ago
First seen on Joblaze 2 months ago
Last verified on the company career page 1 day ago
Skills & Technologies
AI in the day-to-day
You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow.
Requirements
Not disclosed in this posting: years of experience, visa sponsorship.
Benefits
Joblaze summary
In the role of Applied AI Researcher focused on System Self-Construction, the individual will engage in designing innovative architectures that enable systems to autonomously generate and refine their own components. Key skills include expertise in meta-learning, program synthesis, and the ability to build modular systems, with a strong emphasis on practical application over theoretical concepts. This position is ideal for experienced researchers with a proven track record in AI who thrive in a dynamic, mission-driven environment that values creativity and hands-on problem-solving.
Joblaze insights
Quick facts
From the original posting
At Distyl we’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used.
Our researchers come from many academic backgrounds but have strong research track records, operate in an AI-native way, and would be bored staying on the rails of a traditional research org.
The System Self-Construction team builds systems that can build other systems. Researchers design architectures capable of autonomously generating, assembling, and refining sub-systems. This involves developing meta-learning loops, automated pipeline generation, and self-architecting frameworks that reduce the human bottleneck in complex system creation.
Researchers in Self-Construction study recursive design principles: how systems represent their own construction processes, evaluate them, and evolve. They draw from meta-learning, program synthesis, and evolutionary computation to explore what it means for a system to “understand” and redesign itself. Their work defines the frontier of self-referential, generative system architectures.
Experience Building Modular and Composable Systems: You’ve engineered architectures where components interact dynamically (e.g. graph-based planners, agent orchestration frameworks, workflow engines, or automated pipeline builders).
Experience Building with Models, Not Just Building Models: We develop intelligent systems using models rather than training or fine-tuning them. Ideal candidates have expertise in compound AI systems, agentic collaboration, and associated techniques (ensembling, ReAct, graph-of-thoughts, etc.).
Proven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done.
Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow.
Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI.
Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize.
The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package
Flexible time off
Complimentary in-office lunches and snacks provided
Ownership of high-impact projects across top enterprises
#LI-Hybrid
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