Job description

Our mission at Onton is to help people make decisions they love, instantly. We’re tackling the most economically impactful decisions first: the average shopping journey takes 79 days, and we’re taking that to less than 1. Since our public launch in late 2023, we've grown exponentially to guide millions of users to their perfect product. We recently built the foundation of a neurosymbolic AI agent that learns more about the world on every search. You have the chance to solve equally difficult problems as you scale Onton 10x over the next few months to serve 1B+ searches/year, which is just the beginning. YOU HAVE THE OPPORTUNITY TO: - Join Onton as an founding Engineer and set the foundation for our Engineering Team - Design, scope, implement, and deploy user-critical features. - Work with a dynamic team of other engineers, AI researchers, and product designers tackling cutting-edge problems to create a seamless, cohesive experience for users. - Build across every layer of the stack — web app, container, infrastructure, etc. - Stay up-to-date on the latest technologies and techniques to continually enhance our system, yourself, and the rest of the team. WE EXPECT YOU TO: - Have 3+ years of relevant engineering experience, preferably in fast-scaling companies. - Be a self-directed generalist, capable of picking up any engineering problem and solving it, no matter how tedious. - Quickly and iteratively ship code that is correct, robust, scalable, and maintainable. We love elegant code, but we’re not optimizing for that. We take pride in the excellence of the product we build. - Exercise exceptional communication and interpersonal skills. INTERESTING PROBLEMS WE’VE WORKED ON RECENTLY: - Creating our own proprietary graph engine from scratch, which ended up being 700x faster on natural language queries than RedisGraph (a SOTA graph database which outperforms competitors by up to 15,000x on some benchmarks). - Enabling a user to combine text and image queries — for instance, they could upload an image of a blue couch and say “like this, but in green”. To do this, we made our neurosymbolic search engine multimodal. - Automatically making logical sense of a subset of natural language via statistical and symbolic parsing techniques. - Fine-tuning an ensemble of ML models to perform object detection on diffusion-model-generated images. - Building out a performant and scalable inference engine to support more powerful and nuanced natural language queries from our users. WE’D LOVE IT IF YOU: - Enjoy giving high-level abstractions low-level performance. - Have functional programming experience. If not, no problem; motivated engineers learn it quickly. - Have worked with NLP and ML models before and understand their capabilities and limitations. 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. DIVERSITY, EQUITY, INCLUSION, AND BELONGING STATEMENT We hire talented and passionate people from diverse backgrounds to ensure our global workforce reflects our customers. Even if your experience doesn't perfectly match every requirement in the job description, we encourage you to apply. If you're a builder at heart who shares our values and is passionate about making software tools accessible to all, we want to hear from you. Onton is proud to be an equal opportunity employer. We do not discriminate in hiring or employment decisions based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other legally protected characteristics. We consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans during our application process. If you need assistance or an accommodation due to a disability, please contact your recruiter.

Requirements

Must-haves

Join Onton as an founding Engineer and set the foundation for our Engineering Team
Design, scope, implement, and deploy user-critical features.
Work with a dynamic team of other engineers, AI researchers, and product designers tackling cutting-edge problems to create a seamless, cohesive experience for users.
Build across every layer of the stack — web app, container, infrastructure, etc.
Stay up-to-date on the latest technologies and techniques to continually enhance our system, yourself, and the rest of the team.
Have 3+ years of relevant engineering experience, preferably in fast-scaling companies.
Be a self-directed generalist, capable of picking up any engineering problem and solving it, no matter how tedious.
Quickly and iteratively ship code that is correct, robust, scalable, and maintainable. We love elegant code, but we’re not optimizing for that. We take pride in the excellence of the product we build.
Exercise exceptional communication and interpersonal skills.
Enabling a user to combine text and image queries — for instance, they could upload an image of a blue couch and say “like this, but in green”. To do this, we made our neurosymbolic search engine multimodal.
Automatically making logical sense of a subset of natural language via statistical and symbolic parsing techniques.
Fine-tuning an ensemble of ML models to perform object detection on diffusion-model-generated images.
Building out a performant and scalable inference engine to support more powerful and nuanced natural language queries from our users.
Enjoy giving high-level abstractions low-level performance.
Have functional programming experience. If not, no problem; motivated engineers learn it quickly.
Have worked with NLP and ML models before and understand their capabilities and limitations.
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.
DIVERSITY, EQUITY, INCLUSION, AND BELONGING STATEMENT

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

airestml

Platform: ashby
Effort: quick