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Encord

Research Engineer

Posted 26 Days Ago
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In-Office
London, Greater London, England, GBR
Entry level
In-Office
London, Greater London, England, GBR
Entry level
Conduct original research in robotics, computer vision, and multimodal machine learning, focusing on data curation, annotation, evaluation, and quality control. Develop hypotheses, experiments, and end-to-end prototypes for agentic multimodal workflows, video understanding, and 3D applications. Collaborate with ML and product engineering teams to integrate successful research into the platform, shape research strategy, mentor colleagues, and publish findings.
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About us

We're solving AI's hardest problem: alignment.

 

Encord is the data layer for Physical AI and enterprise, serving as core infrastructure for 300+ of the world's leading AI teams, including Woven by Toyota, Hitachi, Skydio, AbbVie and Dyna, Walden and Agility Robotics. From autonomous vehicles and robotics to sports and healthcare, we're solving AI's hardest problem: turning complex, real-world data into production-ready intelligent systems.

 

We're a team of founders, scientists, quants, researchers, and former Olympians, who’ve helped build some of the most successful companies in Silicon Valley, and alumni of MIT, Stanford, UC Berkeley, Oxford, Cambridge, and Imperial. We’ve raised $110M from legendary technology investors, early backers of companies like Databricks, ElevenLabs and Vercel, and we’re growing at an extraordinary pace.

 

We're looking for exceptional people who want to help build a category-defining company, operating with high urgency and taking real ownership to help shape the future of AI.

 
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, commission, and meaningful equity in a high-growth startup

  • Clear, accelerated growth opportunities as the company scales rapidly

  • Strong in-person culture: 4 days/week

  • Daily team lunches & dinners

  • Annual learning & development budget

  • Comprehensive health, dental, and vision coverage

  • US employees: 18 paid vacation days plus US public holidays

  • UK employees: 25 paid vacation days plus UK public holidays

  • Frequent travel opportunities across the U.S., London, and Europe

  • Bi-annual company offsites & monthly socials

 
Operating principles
 

High agency

You see something broken, you fix it or find the person who can. We celebrate the people who solve 90% of a problem before anyone asks.

Build with care & urgency

We bear-hug the customer. Former founders and people from fast-moving, high-stakes environments thrive here.

Self-aware & hungry

We stay warm, self-aware, and genuinely hungry. We elevate our peers, and ego doesn't last long.

Invent in real time

We move toward the ambiguity. We’re pragmatic, resourceful, energized by the fact that there's no playbook.

 

If you're looking to do the most meaningful work of your career alongside people who push you to be better, we'd love to meet you.

HQ

Encord London, England Office

Eastcastle St, London, United Kingdom, W1W 8DE

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