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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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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


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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
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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