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Encord

AI-native data infrastructure for Physical AI

Senior Engineer - High Performance Data Systems

Backend EngineeringUpdated on Nov 13
Full-timeLondon, UK

About the Job

Requirements

  • Fluency in at least one high-level programming language, such as Python or TypeScript, and one imperative statically typed language, such as Rust, C++, Java, Go, or another language.
  • A solid grounding in distributed systems concepts, including databases, replication, partitioning, queuing, caching, and consistency, and how they behave under load.
  • A deep understanding of computer science fundamentals, data structures, and algorithms.
  • Experience owning production services and improving quality through code reviews, testing, rollout, and monitoring.
  • Personal experience developing and maintaining multiple systems from scratch, with an understanding of the trade-offs involved in building reliable, performant software at speed.
  • Ability to combine rigorous engineering with prioritization to ship efficient and correct systems quickly.
  • Ability to tackle problems without a predefined, clear definition or obvious solution and make autonomous decisions.
  • Ability to contribute strong work and help others contribute their best.

Responsibilities

  • Own significant data systems projects end to end, including design, architecture, deployment, monitoring, and measuring impact.
  • Build distributed systems that remain fast and correct under load, and reason carefully about potential failure modes.
  • Shape performant protocols and application programming interfaces that customers build directly on.
  • Find simple solutions to complex domains at scale and choose appropriate technology.
  • Raise the bar for the team through code reviews, pairing, and sharing knowledge.

About the Company

Encord

AI-native data infrastructure for Physical AI

Encord provides an AI-native data infrastructure platform for Physical AI, helping enterprises manage multimodal data for robotics, autonomous systems, and related applications. It offers Encord Annotate for collaborative multimodal annotation, Encord Active for data curation and quality evaluation, and Encord Index for petabyte-scale dataset search and management, covering the full data lifecycle from collection to deployment. The platform acts as a universal data layer for production-grade Physical AI, addressing the infrastructure gap left by cloud-era tools focused on text and tabular data and emphasizing multimodal data and embodied AI. Its goal is to enable teams to build, evaluate, and deploy real-world AI systems more efficiently with scalable, reliable data tooling.

Company size
201-500
Company stage
Series C
Total funding
$107.1M
Headquarters
London, United Kingdom
Founded
2020

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