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Updated 2026-06-20 00:00 UTC·© 2025–2026 RoleSuite
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Machine Learning Engineer

Encord · London

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 are looking for an experienced Machine Learning Engineer to join our team and help us build and scale cutting-edge machine learning and computer vision solutions that power real AI workflows. You'll work hands-on across the full ML lifecycle — from experimenting with the latest models and techniques to integrating them into a production platform used by hundreds of AI teams worldwide.

 

This is a highly collaborative role where you'll partner closely with our product engineering and human data teams to turn complex algorithmic ideas into reliable, scalable features that customers love. Our work is at the cutting edge of computer vision and deep learning, which also includes working on solving unsolved problems within those fields.

If you're someone who thrives at the intersection of strong ML fundamentals and practical engineering, and wants to see their work make a direct impact at scale — this is the role for you.

 

What you'll do

  • Experiment with and adapt the latest ML technologies to fit into our existing tech stack

  • Solve idiosyncratic statistical, geometric, and engineering problems

  • Work closely with a full-stack tech team to assist implementation of research solutions into the product

  • Contribute to hiring additional talent to our rapidly growing team

  • Work with a broad tech stack (e.g. ReactJS, Python, REST & GraphQL, OpenCV, PyTorch, GCP, AWS & CUDA, Kubernetes) and the cutting edge of computer vision and deep learning

     

Who we're looking for

  • Hands-on and experimental — you're comfortable executing on projects end-to-end, running tests, and iterating based on what the data tells you

  • Collaborative by nature — you work closely with engineering and product teams to turn complex algorithmic ideas into reliable, scalable features

  • Driven to solve hard problems — you thrive at the intersection of strong ML fundamentals and practical engineering

  • Bonus: you've led or contributed to applied research teams and have relevant publications to show for it

 

Experience requirements

  • 3+ years of experience in machine learning engineering, with concrete examples of models or systems you've built and shipped

  • Strong experience in Python and ML libraries such as OpenCV, PyTorch, TensorFlow, Fast.ai, and Keras

  • Strong foundation in mathematical programming, algorithmic problem solving, and applied machine learning

  • Bonus: experience in the AI/ML ecosystem and familiarity with computer vision

Why Encord

  • Competitive salary, commission, 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

  • Company lunches twice a week

  • Monthly socials & bi-annual team offsites

AI Engineering pay context

Based on 636 disclosed AI Engineering salaries on RoleSuite, the role pays a median of $200K/year, with most offers between $166K and $239K (10th–90th percentile: $135K–$285K).

See the full AI Engineering salary breakdown →
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Other roles at Encord

  • Human Data Operations StrategistLondon
  • Strategic OperationsLondon
  • General ManagerIndia
  • General Manager, Human Data OperationsBengaluru
  • General ManagerIndia
  • Software Engineer, Physical AISan Francisco
  • Senior Software Engineer, Full-StackSan Francisco
  • Software Engineer, Full-StackSan Francisco
  • Software Engineer, Applied AISan Francisco
  • Commercial Associate, Physical AINew York

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