Mistral AISingapore
EncordPosted 5mo ago
Strategic Projects Lead at Encord scores 73 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
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
As a Strategic Projects Lead, you'll fully own and optimize the data annotation and machine learning workflows behind Encord's largest client relationships. You'll work directly with clients, annotation specialists, ML engineers, Account Managers, and Forward Deployed Engineers to ensure the data powering their models is fast, accurate, and scalable.
This is a hands-on, high visibility role. You have direct influence on whether Encord's highest-value customers renew and expand.
What you'll do
Own data annotation projects end-to-end, translating complex AI/ML requirements into clear workflows and instructions for annotation teams
Design and refine annotation processes, audit results, and build feedback loops that raise data quality
Act as a trusted advisor to clients — designing and implementing the human-annotation workflow that gets them to production fastest
Partner with product and engineering to drive improvements in AI training data tools and methodology
Directly influence account health: your workflow design and execution are a primary driver of whether strategic accounts renew, expand, or churn
Who we're looking for
A sharp, execution-oriented operator with a consulting or AI-company pedigree . A structured thinker, strong PM instincts, bias for getting things done
Analytically rigorous and comfortable with ambiguity. You break down operational problems from first principles
Technically fluent: comfortable querying a database, auditing annotation outputs, or automating a workflow in Python
A natural translator between ML engineers and non-technical clients on multi-stakeholder projects
Entrepreneurial — you take ownership without waiting to be told what to do
Experience requirements
3–7 years of professional experience, with a strong preference for backgrounds in top-tier strategy consulting and/or operations or data roles at leading AI or technology companies
Proven ownership of complex, multi-stakeholder workflows end-to-end: scoping, execution, QA, iteration
Experience designing/optimizing data operations with an eye for quality, consistency, and scalability, ideally human-in-the-loop or structured labeling work
Demonstrated ability to engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients, translating requirements clearly in both directions
Bonus: hands-on experience with computer vision, generative AI, or multimodal data workflows; prior exposure to data annotation platforms or quality management frameworks; experience coaching or managing operational teams
Bonus: Working proficiency in Python or SQL, with the ability to query data, automate workflows, or audit annotation outputs; broader familiarity with relational databases or data annotation tooling equally valued
Why Encord
Competitive salary, commission, and meaningful equity in a high-growth start-up
Clear, accelerated growth opportunities as the company scales rapidly
Strong in-person culture: 4 days/week
Flexible PTO to fully recharge
Annual learning & development budget
Comprehensive health, dental, and vision coverage
Frequent travel opportunities across the U.S., London, and Europe
Bi-annual company offsites, twice-weekly team lunches, and monthly socials
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you keep labeling instructions consistent across a large annotation team?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI Data Labeling and Computer Vision. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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