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Research Engineer

Salary not disclosedOnsite

  • Engineering
  • London
  • Full time
  • Today
Newly posted

About the role

Encord is seeking a Research Engineer to join the ML team to work on robotics, computer vision, and multimodal research. You will focus on data curation, annotation, evaluation, and quality control, with the goal of integrating research findings into the core product. The role involves forming hypotheses, designing experiments, and building prototypes to solve complex problems for frontier AI and robotics customers.

Responsibilities

  • 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

Required skills

  • Computer vision
  • Multimodal ML
  • Statistics
  • Probability
  • Linear algebra
  • Python
  • PyTorch
  • Data-centric AI

Nice to have

  • LLM-based agents
  • Video processing
  • 3D data

Qualifications

  • PhD in computer vision, machine learning or a related field
  • Equivalent applied research experience

Benefits

  • Competitive salary
  • Equity
  • 25 days annual leave
  • UK public holidays
  • Annual learning & development budget
  • Travel for customer visits, events, and conferences
  • Daily company lunches
  • Monthly socials
  • Bi-annual team offsites

About the Company

Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. The platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production.