Staff Research Engineer

Onton

• $150K — $180K *
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of software, ML, or research engineering experience
  • Deep understanding of current AI landscape, particularly neurosymbolic approaches
  • Experience in AI research projects with empirical contributions
  • Preference for hands-on implementation over theoretical research
  • Excitement for non-purely-statistical AI methodologies
  • Desire to work in collaborative, fast-paced environments
  • Ability to ship robust, scalable, and maintainable code quickly

Responsibilities

  • Develop AI agents capable of optimizing decision-making processes
  • Collaborate with a team to enhance neurosymbolic architecture
  • Conduct self-driven experiments to innovate AI solutions
  • Iteratively refine code based on performance metrics
  • Resolve fundamental AI challenges related to context and memory
  • Engage in collaborative projects rather than solo endeavors

Benefits

  • Full-time, onsite work in San Francisco emphasizing teamwork
  • Relocation compensation offered for candidates moving to the area
  • Opportunities for transition to fully remote work after one year of employment
Full Job Description
Your opportunity

Together we will create an AI agent capable of providing a person, or itself, with sufficient context to make optimal decisions as quickly as possible. This agent will ultimately be capable of superseding most things we do at Onton.

Our current application of e-commerce, making an optimal purchase decision - considering user preferences, millions of products, and billions of reviews - already requires a world model and a logical consistency far beyond the state of the art.

Even OpenAI's GPT-5.6 can't rid itself of the problem of hallucination, and there are no sufficiently robust bolt-on solutions for context finiteness (RAG is not enough), catastrophic forgetting, or many other fundamental problems afflicting current-gen AI systems. Contra OpenAI, we believe that scale is not all you need. These challenges can only be addressed at the architectural level.

Recently we've built the foundation of a neurosymbolic AI agent that learns more about the world on every search. It's still in its infancy, but its compositionally-grounded architecture shows promise as the basis of a truly general problem solver. With your ingenuity - realized through your self-directed, data-driven experiments from first principles - we can turn its sparks of intelligence into a fire.
We expect you to
  • Have significant software, ML, or research engineering experience
  • Command a deep, principled understanding of the current state of the field of AI, especially neurosymbolic approaches.
  • Have some experience contributing to empirical AI research projects
  • Enjoy implementation, not just writing papers.
  • Be excited about non-purely-statistical approaches to AI.
  • Prefer fast-moving collaborative projects to extensive solo efforts.
  • Quickly and iteratively ship code that is correct, robust, scalable, and maintainable. We're not optimizing for novelty, academic recognition, or theoretical purity. Recognition will come easily from the excellence of the product we build.
We'd love it if you:
  • Have a PhD or Master's in Artificial Intelligence, Computer Science, Cognitive Science, Linguistics, or comparable (or equivalent research experience).
Onsite Interviews

Our final round of interviews is conducted onsite at our SF office, and this role requires full-time, in-person collaboration. We believe that the best work happens when our team is together, fostering creativity, spontaneous collaboration, and strong relationships.

If you're unable to attend the interviews onsite or work onsite full-time, this position may not be the right fit. We want to ensure all candidates have a clear understanding of our work environment before applying, so everyone's time is respected throughout the process.
Location

Our team works in hybrid, 3 days a week, in our new office in San Francisco (Jackson Square). We're offering relocation compensation as we build density in this area.

We have a tenure system where, after a year, any team member can transition to a fully remote, provided they operate primarily on Pacific Time.

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