Nir Ben Zvi

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Professional Experience

Deep Learning Freelancer (2021-present)

  • Freelance computer vision and NLP applied researcher working on the cutting edge.
  • Owning the full machine learning development lifecycle—problem definition, data pipeline design, model development, evaluation, and production deployment.
  • Writing production-grade code for generative image models and large language models, as well as object detection, semantic segmentation, knowledge graph traversal, agentic flows, and more.
  • Acting as a technical leader and hands-on contributor, driving ML strategy and execution across diverse organizations.
  • Building research-driven solutions beyond off-the-shelf models, with measurable business impact.
  • Partial list of clients:
    Mixtiles, Simply, Deci.AI, Lemonade, DeepChecks, CommonGround, Papaya-Global and KLA-Tencor.

Computer Vision Research Manager, Trigo (2018-2021)

  • Part of the founding team and the first computer vision hire.
  • Built Trigo’s first deep learning models from scratch, running in real-time in live supermarkets.
  • Led development of object detection and real-time tracking models optimized for deployment.
  • Scaled machine learning R\&D from garage phase (<10 employees) to 100+ employees, hiring and growing top-tier ML researchers and engineers.
  • Built annotation pipelines, ML infrastructure, and model evaluation tools to support large-scale CV development.

Computer Vision Research Scientist, Amazon Lab126 (2015-2018)

  • Researched, trained and deployed computer vision models for Amazon’s consumer devices, including the Echo Look and the Echo Show.
  • Led research efforts for the group’s first deep-learning-based object detection models used in production.
  • Worked end-to-end on ML research, from whiteboard concepts to production-grade implementations in Amazon products.
  • Key deep learning research and infrastructure evaluator within the team, staying ahead of cutting-edge developments.
  • Participated and contributed to Amazon’s (discontinued) MXNet deep learning framework.

Computer Vision Algorithm Engineer, Donde Search (Acquired by Shopify) (2015)

  • Coded Donde’s first visual search engine using Caffe.

Imagineer, Disney Research (2013-2014)

  • Research associate under supervision of Prof. Arik Shamir.
  • Researched style-transfer algorithms based on real artist data (pre-deep learning).
  • Developed image contour tracking models for artistic style transfer.

Education

  • M.Sc, Computer Science, The Hebrew University of Jerusalem (2013 – 2015)
  • B.Sc, Computer Science, The Hebrew University of Jerusalem (2010 – 2013)
  • Minor in Visual Communications, Bezalel Academy of Art and Design (2010-2014)

Publications

Alexander Lorbert, Nir Ben-Zvi, Arridhana Ciptadi, Eduard Oks, Ambrish Tyagi
Toward Better Reconstruction of Style Images with GANs
KDD2017 Workshop on Fashion AI

Nir Ben-Zvi, Jose Bento Ayres Pereira, Moshe Mahler, Jessica Hodgins, Arik Shamir
Line-Drawing Video Stylization
Eurographics 2016

Other

Teaching

  • TA in ‘Object Oriented Programming’, The Hebrew University of Jerusalem (2014)
  • Deep Learning CS231 Community Course, Google Campus (2017-2020)

Military Service

Full military service in the elite unit of the IDF artillery corps, “Moran” (2006-2009)

  • Squad-commanders course graduate.
  • Reserves duty: In charge of the unit’s assessments of new recruits (“gibush”).

Code/Tools

  • 10+ years of experience writing Python research and production code on top of POSIX systems.
  • Data processing; postgresql (inc. pgvector), bigquery, snowflake as well as current vector-dbs.
  • Thorough knowledge of deep learning hardware, compute pipelines, and model throughput optimization (ONNX, TRT, etc.).
  • Full proficiency with common 3D, video and image editing tools (Blender, Photoshop, Lightroom, Illustrator).

Inter/Personal

  • Full fluency within an English working environment; Native Hebrew speaker.
  • Ex-professional Photographer.
  • A generally nice guy.