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Encord

computer vision

Encord is the multimodal data layer for physical AI. Manage, curate, annotate, and align petabytes of data - from sensor streams to video to text. Trusted by 300+ AI teams including Woven by Toyota, AXA, UiPath, Zipline, and more.

Toboroz a(z) Encord?

Igen. 2026. október 11. állapot szerint a(z) Encord cégnek 38 nyitott pozíciója van a Metaintrón.

Nyitott pozíciók

A legújabbak elöl. A fizetést akkor mutatjuk, ha a hirdetés tartalmazza.

Ügyfelek

Mind a 36 cég, amelyet a(z) Encord ügyfélként nevez meg.

Most toborzó ügyfelek13

Esettanulmányok16

További ügyfelek7

Mit mondanak az ügyfeleik

Idézetek a(z) Encord ügyfeleinél dolgozóktól.

“Encord helps us to offer a ‘best in class’ capability for counting trees. It has helped us to improve the computer vision algorithm that allows us to delineate individual tree tops. [We were able] to count the entire forest in two minutes as opposed to two weeks.”

Robert Godfrey · Treeconomy

““We went through a bunch of vendors and one of the things that stood out about Encord was the video first support, which other vendors do not have. Specifically understanding how the video works behind the scenes: the encoding, the frame indexes and square pixel ratios.””

Anurag Kanungo · Voxel

““ We plan on leveraging Encord to expand the range of use cases and include more medical conditions in our solutions… We are excited about our potential with Encord and look forward to seeing how we will evolve together in the future.””

Viz.ai

““The division of tasks and clear role assignment ensures organized workflows and the ability for team members to consult certain cases with experts along the way.””

Maayan · Viz.ai

““The interpolation tool is a sophisticated, semi-automatic labeling tool that has proven to be a significant time saver for our team by reducing labeling time and improving precision.””

Maayan · Viz.ai
További 24 idézet mutatása

““Encord constantly impresses us with the ability to think outside the box,””

Maayan · Viz.ai

““The annotation platform is well designed for compatibility and interpretability. We were able to effectively align it with the current systems,””

Sarit Meshesha · Data Manager · Viz.ai

““ Encord’s robust support system has been remarkable. Whenever questions or issues come up, they are always supportive and helpful. This ensures that our workflows remain uninterrupted,””

Maayan Gerbi · Clicinal AI Specialist · Viz.ai

“For our AI initiatives, rapid iteration is critical. Encord and our ML infrastructure allow us to  prototype learning tasks efficiently. The composability of Encord enables us to merge diverse data sources, facilitating extensive experimentation. With a well-integrated SDK, it's a matter of a few lines of code to achieve seamless integration and functionality.”

Matt Pearce · Applied ML · Pickle Robot

“The UX on Encord's platform was way more clear as to how everything comes together.”

Evgeny Nuger · OnsiteIQ

“By implementing Encord within our redesigned ML infrastructure, we've established an efficient end-to-end workflow from data sampling through to model training.”

Evgeny Nuger · Principal Engineer · OnsiteIQ

“Encord integrates seamlessly into our entire AI infrastructure,”

Evgeny Nuger · Principal Engineer · OnsiteIQ

“With the model assistance, we found a much higher increase in efficiency within Encord simply because most labels were produced by a trained model and did not require correction.”

King's College London

“Products like Encord are going to help us do that because they’re allowing us to unlock the potential of that data faster and in a more democratising way.”

Dr. Bu Hayee · Director for Gastroenterology and Endoscopy · King’s College Hospital

“The interface is intuitive, so it requires very little training to become a sort of “expert” at using all the functionality.”

Dr. Bu Hayee · Director for Gastroenterology and Endoscopy · King’s College Hospital

“Compared to other label assistance tools that we’ve worked with, Encord’s user experience is much smoother.”

Dr. Bu Hayee · Director for Gastroenterology and Endoscopy · King’s College Hospital

“With Encord, we annotated the data over six times faster than using traditional methods.”

Dr. Bu Hayee · Director for Gastroenterology and Endoscopy · King’s College Hospital

““Using Encord has more than halved the time it takes us to provide feedback on imagery. What could have previously taken us 2 hours now takes approximately 30 minutes.””

Mira Murali · Computer Vision Engineer · Four Growers

““The fact that Encord was able to offer both an automatic labeling tool as well as a team of annotators that we could use was very attractive. We need that flexibility at this stage in our journey,””

Murali · Four Growers

““The labeling speed of the annotation team improved to almost 60% compared to when using their in-house tool.””

Markus Kittel · CONXAI

““With other labeling tools, we needed to integrate another tool for data management and exploration capabilities, but Encord combined the two needs and provided a single comprehensive solution, along with excellent customer care and support,””

Markus Kittel · AI Product Development Manager · CONXAI

“With Encord, myself and other team members can label the data ourselves. We have numerous projects that we want to achieve this year, and I think having an easy to use platform where we can all work together is going to help us move them forward quickly and successfully,”

Elmes · The Far Out Thinking Company

“We built separate pipelines for the three sets of images and labeled them accordingly. Then we trained and tested this small model. We got really good results, and it took more time to pull the images off the internet than it did to label them and build the model,”

Elmes · The Far Out Thinking Company

“After they helped us put the images together, we pressed a couple of buttons, and the platform made a model for us,”

Elmes · The Far Out Thinking Company

“We could also do computation both on the cloud and locally on our deep learning machine. All those factors made it really advantageous for us, and I saw the opportunity to save a lot of time and costs by using Encord to speed up our model development.”

Mathew Elmes · Director · Pollenize

“The platform was so intuitive. It provides a lot of different levels of control and team management. Everyone on the team could label and review images easily,”

Mathew Elmes · Director · Pollenize

“It's a very easy platform to operate. What I really liked was the whole offering of Encord for both automated labeling and manual work, as precision is incredibly important to us.”

Konstantina Kaisheva · Neurons

““Encord’s team has been very hands-on in delivering what we need to succeed,” says Camilla. “A lot of companies promise that level of commitment, but Encord actually delivers it. We receive excellent support. They build out new features quickly based on our feedback. With other platforms, we’ve had to troubleshoot problems on our own– even to the extent that we basically needed to build our own offline tooling to process the data we labeled using them! Encord has worked with us to find a solution for every challenge."”

Camilla Gilchrist · Head of Operations · Tractable

““Encord speeds up annotation while still allowing for strong quality control.””

Camilla Gilchrist · Head of Operations · Tractable

MI-bevezetések és partnerek

Mit vezetett be a(z) Encord, és kikkel dolgozik együtt az MI terén.

  • BevezetésAI-native data infrastructure platformEncord offers an AI-native data infrastructure platform for production-scale AI systems.
  • BevezetésLiDAR AnnotationEncord offers LiDAR annotation tools that combine LiDAR point clouds with vision data for autonomous vehicles, robotics, and spatial AI applications.
  • BevezetésLLM-Powered AnalysisEncord lets users trigger LLM agents to grade content quality across multiple criteria.
  • BevezetésLLM as a JudgeEncord lets users deploy LLM judges to grade model outputs, identify failures, and accelerate model iteration cycles for production readiness.

Állásinterjúk

Hogyan írja le a(z) Encord a kiválasztási folyamatát.

“It varies by role and team, but the general shape is: recruiter screen, hiring manager conversation, a skills-based interview or take-home, and a final panel.”

Keresett készségek

A leggyakoribbak a nyitott hirdetésekben.

Technológiai stack

Tartalomkezelő
Prismic
HubSpot CMS
Keretrendszerek
Gatsby
Analitika
Google Analytics 4
Google Tag Manager
Marketing
HubSpot
Tárhely
Amazon Web Services
Könyvtárak
Tailwind CSS
GSAP
D3.js
Swiper

Cégadatok

Iparág
computer vision
Ágazat (NAICS)
Információ és kommunikáció
Hasonló cég
Matroid
Weboldal
encord.com
Közösségi média
LinkedIn · GitHub · X · YouTube

Pozíciók helyszín szerint

Hol toboroz a(z) Encord. Válassz egy várost a pozíciói megtekintéséhez.

Hasonló cégek

A(z) Encord iparágában működő cégek, amelyek most toboroznak.

Kérdések a(z) Encord cégről

Toboroz a(z) Encord?
Igen. 2026. október 11. állapot szerint a(z) Encord cégnek 38 nyitott pozíciója van a Metaintrón. A legtöbb ezekben a csapatokban van: Developer (10), Sales (9) és Product/Project Management (5).
Hol toboroz a(z) Encord?
A(z) Encord a következő városokban toboroz: London, San Francisco, New York és India. A legtöbb nyitott pozíció helyszíne: London.
Milyen a kiválasztási folyamat a(z) Encord cégnél?
A(z) Encord így írja le: „It varies by role and team, but the general shape is: recruiter screen, hiring manager conversation, a skills-based interview or take-home, and a final panel.”
Kik a(z) Encord ügyfelei?
A(z) Encord 36 ügyfelet nevez meg, köztük: mayo clinic, Neura robotics, Woven by Toyota, UiPath és Weave.
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