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Reimagining online commerce search

Tonita is an early-stage AI startup. We're building a technical stack for commerce search from the ground up. Our magic ingredient is natural language understanding.

We are hiring

We're looking to add top talent to our core engineering team. We're keen to build a team with diverse styles, perspectives, backgrounds; a lot of energy and willingness to learn and have fun!
Jobs are US-based (hybrid), primarily in New York City and the Bay Area; remote work is a possibility for exceptional candidates based in the US or Canada.
If you’re interested, please send your resume to
Please include a paragraph about which role you’re interested in, what excites you about Tonita, and what’s unique about you!

A bit about Tonita

We believe that commerce search should be simple, beautiful, and effortless

To realize this vision, we are building a foundational technical stack for commerce search. Our magic ingredient is natural language understanding, working in concert with algorithmic techniques for information extraction and semantic understanding of structured and semi-structured information.

We are a well-funded early-stage AI startup

Tonita was founded by ex-Googlers with years of experience across computer science, from building mission-critical infrastructure to cutting-edge AI and machine learning.

Our tech stack is cutting-edge

Tonita's platform built on the modern NLP stack, including: deep learning with PyTorch; Kubernetes, Apache Beam, Google Cloud; Python, C++ / Rust, Flutter / Dart, Firebase.

Led by experts in Search, Advertising, and AI

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Uma Mahadevan

Expert in search advertising infrastructure and quality; lead engineer for Google's advanced broad match paradigm in search advertising; PhD in computer vision.
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D. Sivakumar

Scientist with deep expertise in AI and algorithms; Engineer with loads of experience in search, discovery, and recommendations algorithms.

Open roles

Search Quality Engineer

Strong experience in information retrieval, information / structured data extraction, embedding-based retrieval, ranking algorithms, and other “quality” aspects of search/discovery.

Infrastructure Engineer

Expertise in scalable API design, implementation, and production on Cloud platforms. Experience with Cloud-based ML/AI in a SaaS offering: ML serving, logging/feedback as first-class citizens for continuous learning pipelines. Hands-on experience with monitoring, CI/CD, Cloud and ML DevOps

NLP Researcher / Engineer

Solid understanding of the fundamentals of deep learning and deep NLP; ability to create innovative solutions for natural-language problems using state-of-the-art tools (Transformers, BERT, GPT, CLIP, HuggingFace, PyTorch, …), and creativity needed for designing NLP solutions in data-sparse and text + structured data scenarios.