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Encord is a universal data layer for AI serving 300+ AI teams. The platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Customers include Woven by Toyota, AXA, UiPath, and Zipline. The company has raised $60M in Series C funding and operates a team of 100+ people.
As a Research Engineer on the ML team, you will drive original research on open problems sourced from leading robotics and physical AI customers. Your work will span robotics, computer vision, and multimodal research with a focus on data curation, annotation, evaluation, and quality control. Successful research will be integrated into the core product.
Key responsibilities include:
- Forming hypotheses, designing experiments, and conducting original research on open problems from frontier customers
- Researching and prototyping agentic workflows that handle multimodal inputs and diverse customer ontologies
- Advancing data curation and model evaluation capabilities
- Working on egocentric video understanding, including captioning and 3D understanding
- Building working prototypes to test ideas end-to-end, then partnering with ML systems and Product Engineering teams to productionize them
- Shaping longer-term research direction and bringing relevant ideas from the field to the team
- Publishing research papers and presenting work at conferences and workshops
The role requires a builder with a research mindset who can take open-ended problems and drive them to working prototypes. You should be a first-principles problem solver with strong fundamentals, a big-picture thinker excited by ambitious longer-term problems, and a multiplier who raises the level of the team through mentoring and turning findings into decisions.
The team works from the London office 4+ days per week, with a strong in-person culture. Benefits include 25 days annual leave plus UK public holidays, annual learning & development budget, travel for customer visits and conferences, daily company lunches, and monthly socials with bi-annual team offsites.
Requirements:
- PhD in computer vision, machine learning, or related field, OR equivalent applied research experience
- Strong background in computer vision and multimodal ML (traditional CV, modern VLMs, embedding models, or both)
- Clear evidence of independent research: publications, thesis, open-source work, or applied research with original contribution
- Solid mathematical foundations in statistics, probability, and linear algebra
- Strong Python and PyTorch skills with experience running experiments end-to-end
- Genuine interest in data-centric AI: curation, evaluation, and data quality
- Bonus: experience with LLM-based agents applied to visual tasks, or working with video, 3D, or other complex data types
