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.
Stellt gerade ein
Stellt Encord ein?
Ja. Stand 2. Oktober 2026 hat Encord 46 offene Stellen auf Metaintro.
Offene Stellen
Neueste zuerst. Gehalt, sofern in der Anzeige angegeben.
- Lead Security EngineerSicherheitLondon · Vor OrtLondonVor Ort—gestern
- Quant Developer in AIEntwicklerLondon · Vor OrtLondonVor Ort—vorgestern
- Senior Product Marketing ManagerMarketingSan Francisco · Vor Ort · $140K – $180K/yrSan FranciscoVor Ort$140K – $180K/yrvorgestern
- GTM Recruiter AssociatePersonal/TalentakquiseSan Francisco · Vor OrtSan FranciscoVor Ort—vor 3 Tagen
- Recruiting EngineerPersonal/TalentakquiseSan Francisco · Vor OrtSan FranciscoVor Ort—vor 3 Tagen
- Senior Engineer - High Performance Data SystemsEntwicklerLondon · Vor OrtLondonVor Ort—vor 4 Tagen
- Product LeadProdukt-/ProjektmanagementLondon · Vor OrtLondonVor Ort—vor 4 Tagen
- DevOps EngineerDevOpsLondon · Vor OrtLondonVor Ort—vor 10 Tagen
Kunden
Alle 24 Unternehmen, die Encord als Kunden nennt.
Kunden, die gerade einstellen5
- mayo clinic2.931 offene Stellen
- Woven by Toyota137 offene Stellen
- Zipline21 offene Stellen
- ANYbotics17 offene Stellen
- Voxel9 offene Stellen
Fallstudien12
Weitere Kunden7
- Pollenize
- Neura robotics
- AXA
- Ui Path
- Twelve labs
- Dyna
- Path Robotics
Was ihre Kunden sagen
Zitate von Personen bei Kunden von Encord.
“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.”
“By implementing Encord within our redesigned ML infrastructure, we've established an efficient end-to-end workflow from data sampling through to model training.”
“Encord integrates seamlessly into our entire AI infrastructure,”
““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.”
““Managing QA workflows efficiently and having an overview of the entire annotation process has been so important for our success. The more manual that QA process is, the more the amount of work explodes as the annotation workforce scales,” explains Camilla. “It’s always about balancing speed and quality. A lot of platforms prioritize speed over quality or quality over speed. Encord speeds up annotation while still allowing for strong quality control.””
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““As our ambition grew, we realized that the functionality of many of the tools we were using was quite limited,” says Camilla Gilchrist, Head of Operations at Tractable. “We had a lot of steps in our annotation workflows, with many different pipelines, and the platforms couldn’t handle that complexity. We also had a bottleneck around quality assurance. With image segmentation, you can’t do a quick agreement rate analysis and doing a manual quality assurance check on each piece of data isn’t feasible. We needed a far more efficient way to assess quality.””
“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.”
“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.”
““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.””
““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,””
““The labeling speed of the annotation team improved to almost 60% compared to when using their in-house tool.””
““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,””
“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,”
“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,”
“After they helped us put the images together, we pressed a couple of buttons, and the platform made a model for us,”
“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.”
“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,”
KI-Produktstarts und Partner
Was Encord auf den Markt gebracht hat und mit wem es bei KI zusammenarbeitet.
- ProduktstartLLM as a JudgeEncord offers a platform to deploy LLM judges to grade model outputs, identify failures, and accelerate model iteration cycles for production readiness.
- ProduktstartLiDAR AnnotationEncord offers 3D annotations combining LiDAR point clouds with vision data for autonomous vehicles, robotics, and spatial AI applications.
- ProduktstartAI data development platformEncord is an AI data development platform for computer vision and multimodal AI teams.
- ProduktstartAI data management and annotationEncord lets users manage, curate, and annotate AI data with customizable multimodal workflows and native agent integrations.
Vorstellungsgespräche
Wie Encord seinen Bewerbungsprozess beschreibt.
“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.”Gefragte Fähigkeiten
Am häufigsten in offenen Stellenanzeigen.
Tech-Stack
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Unternehmensdaten
- Branche
- computer vision
- Branche (NAICS)
- Information und Kommunikation
- Vergleichbares Unternehmen
- Matroid
- Webseite
- encord.com
- Karriere
- encord.com/careers
Stellen nach Standort
Wo Encord einstellt. Wählen Sie eine Stadt, um die Stellen dort zu sehen.
Fragen zu Encord
- Stellt Encord ein?
- Ja. Stand 2. Oktober 2026 hat Encord 46 offene Stellen auf Metaintro. Die meisten entfallen auf Developer (13), Sales (8) und Product/Project Management (3).
- Wo stellt Encord ein?
- Encord stellt in London, San Francisco, New York und India ein, die meisten offenen Stellen gibt es in London.
- Wie läuft der Bewerbungsprozess bei Encord ab?
- Encord beschreibt ihn so: „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.“
- Wer sind die Kunden von Encord?
- Encord nennt 24 Kunden, darunter mayo clinic, Woven by Toyota, Zipline, ANYbotics und Voxel.