---
title: 'Research Engineer at Encord'
canonical: 'https://feeny.ai/job/research-engineer-encord-london-qt7497ayjd63'
type: 'job'
last_seen: '2026-10-17'
---

# Research Engineer at Encord

- **Company:** Encord
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-12
- **Last confirmed live:** 2026-10-17
- **Apply:** https://jobs.ashbyhq.com/encord/19de3b55-70ac-4960-afaf-f488d46acaef

## Job description

## About us

Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator.

## The role

We're looking for a Research Engineer to join Encord's ML team. You'll work on robotics, computer vision and multimodal research in data curation, annotation, evaluation and quality control, with successful work going into the core product.

We face a variety of interesting research problems across the full data life-cycle, including annotation, quality control, verification and curation. We are looking to strengthen our team to build upon and extend our market-leading platform. The kind of problems we solve are constantly evolving alongside the needs of our frontier customers, including many of the leading robotics and physical AI teams. Join us as we leverage our massive flow of proprietary data on our journey to develop generalised solutions applicable across diverse multi-modal tasks.

## What you'll do

- Form hypotheses, design experiments, and drive original research on open problems from leading robotics and AI customers
- Research and prototype agentic workflows which can handle multimodal inputs and diverse customer ontologies
- Advance our work on data curation and model evaluation
- Tackle egocentric video understanding, from captioning to deeper 3d understanding
- Build working prototypes to test ideas end to end, then partner with our ML systems and Product Engineering teammates to bring them into the platform
- Help shape our longer-term research direction and bring the most relevant ideas from the field back to the team
- Publish research papers and present your work at conferences and workshops

Who we're looking for

- A builder with a research mindset. You can take an open-ended problem, form a hypothesis and get to a working prototype without a detailed spec.
- A first-principles problem solver. You lean on strong fundamentals rather than surface-level familiarity with the latest trends.
- A big-picture thinker. You're excited by ambitious, longer-term problems and know how to break them into steps.
- A multiplier. You raise the level of the team around you by shaping research direction, mentoring others and turning findings into decisions.

## Experience requirements

- A PhD in computer vision, machine learning or a related field, or equivalent applied research experience
- A strong background in computer vision and multimodal ML, whether in traditional CV, modern VLMs and embedding models, or both
- Clear evidence of independent research, such as publications, a thesis, open-source work or applied research where you owned the original contribution
- Solid mathematical foundations in statistics, probability and linear algebra
- Strong Python and PyTorch skills, and experience running experiments end-to-end
- A genuine interest in data-centric AI: curation, evaluation and data quality
- Bonus: experience applying LLM-based agents to visual tasks, or working with video, 3D or other complex data types

We’ll start reviewing applications from 1 November 2026. It may take a little while to hear back, but every application will get proper consideration.

## Why Encord

- Competitive salary and meaningful equity in a high-growth startup
- Strong in-person culture — most of the team works from our London office 4+ days/week
- 25 days annual leave + UK public holidays
- Annual learning & development budget
- Travel for customer visits, events, and conferences across the UK and Europe
- Daily company lunches
- Monthly socials & bi-annual team offsites

## About Encord

## Company Overview
- **One-liner**: Encord provides the data infrastructure layer for physical AI, helping teams curate, annotate, evaluate, and manage multimodal training data for systems like autonomous vehicles, robotics, and smart infrastructure.
- **Entity Type**: Private (Venture-backed, $110M total funding)
- **Headquarters**: San Francisco, California, United States (with offices in New York, NY and London, UK)
- **Founded**: 2021
- **Founders**: Ulrik Stig Hansen (CEO/Co-Founder), Eric Landau (Co-Founder & President)

## Core Business
- **Primary industry**: AI infrastructure / Data annotation & curation for Physical AI (autonomous vehicles, robotics, world models, industrial automation)
- **Target customers**: Enterprise AI teams building multimodal, sensor-heavy AI systems (B2B, Enterprise)
- **Mission/purpose**: "Train and run AI on the right data" – solving the data quality bottleneck that prevents AI products from reaching production.

## Products & Services
- **Encord Platform**: End-to-end data management platform covering curation, annotation (native video, LiDAR, audio, text, sensor fusion), RLHF alignment, and model evaluation. API/SDK-first, zero data migration, runs on the customer’s cloud.
- **Data-as-a-Service (DaaS)**: Professional services for data collection and annotation, including in-field operators and teleoperation facilities matched to physical AI tasks.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Total funding $110.1M (as of 2026); annual revenue estimated at $5.5M (LinkedIn proxy, "Not publicly available" for official numbers)
- **Notable Investors/Partners**: CRV, Y Combinator (W21 batch), and individual investors like Luc Vincent (former VP of AI at Meta). Customers include Toyota, Skydio, Maxar, and UiPath (UiPath achieved near 99% model accuracy and 10x dataset growth using Encord).
- **Growth Signals**: 139 employees (+74.3% YoY, +78 people); 300+ teams using the platform; operates in 7 countries; recognized as one of the fastest-growing companies in the data annotation space; strong customer retention (e.g., UiPath 4x reduction in error rate).

## Competitive Advantages
- **Built for Physical AI**: Multimodal by design from the ground up – handles synchronized LiDAR, camera, radar, depth, force/torque, audio, and text in a single workflow.
- **Enterprise‑grade trust**: Zero data migration (data stays in customer cloud), API/SDK-first integration, label lineage and quality controls for production scale.
- **Proven at scale**: Used by leading autonomous vehicle, robotics, and enterprise AI teams; validated by public case studies (UiPath, Toyota, Skydio).

## Strategic Focus
- Deepen capabilities for world models, VLA (Vision-Language-Action) models, and robotic perception.
- Expand Data-as-a-Service offerings for physical AI data collection and annotation.
- Continue scaling the customer base across industrial, manufacturing, autonomous vehicles, and smart infrastructure verticals.

## Why Work Here
- **Culture**: “Strong in-person culture” with hybrid/office‑first approach (San Francisco, New York, London). 45+ nationalities represented. Core values: “Builds with care + urgency” and “High agency”.
- **Compensation & Benefits**: Equity in a hyper‑growth startup; 25 days paid time off; private health insurance (UK/US); team lunch twice a week; monthly team events and bi‑annual offsites; cycle to work scheme; home & tech scheme; annual learning & development stipend; payroll giving scheme.
- **Visa Policy**: Case-by-case visa sponsorship, confirmed early in the recruiter screen.
- **Interview Process**: Typically 4–5 stages: recruiter screen, hiring manager conversation, skills‑based interview or take-home, and final panel. Recruiter walks candidates through specifics upfront.
- **Early‑career programs**: Commercial Associate program (GTM launchpad) and early‑career engineering/ML roles – no formal internship program but hires ambitious early‑career candidates.

## Sources
1. [encord.com – Careers page](https://encord.com/careers)
2. [encord.com – Homepage](https://encord.com/)
3. [encord.com – About page](https://encord.com/about-us/)
4. [linkedin.com – Encord company page](https://es.linkedin.com/company/encord-team)
5. [ycombinator.com – Encord jobs](https://www.ycombinator.com/companies/encord/jobs)

## Other roles at Encord

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- [Product Engineer, DaaS](https://feeny.ai/job/product-engineer-daas-encord-san-francisco-f6gesst71key) — San Francisco, CA
- [Lead Security Engineer](https://feeny.ai/job/lead-security-engineer-encord-london-fj2ez55e8f2a) — London, United Kingdom
- [Senior Product Marketing Manager](https://feeny.ai/job/senior-product-marketing-manager-encord-san-francisco-h8ysd3hz9xy0) — San Francisco, CA
- [Quant Developer in AI](https://feeny.ai/job/quant-developer-in-ai-encord-london-t65rb61mhqm0) — London, United Kingdom
- [Recruiting Engineer](https://feeny.ai/job/recruiting-engineer-encord-san-francisco-drbf5mvebenk) — San Francisco, CA
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