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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.
Team-members

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.