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Technical Content Lead

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Encord

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Location:
United States , San Francisco

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Job Description:

About The Role: How do AI teams detect edge cases faster? What’s the best way for AI leaders to measure annotation pipeline performance? As our Technical Content Lead, you'll translate challenges you've likely faced yourself - dataset quality issues, annotation workflows, model performance issues - into content that resonates with AI and ML teams. You'll bring hands-on experience from data ops, ML engineering, or data infrastructure. You understand dataset quality issues, annotation workflows, and model performance issues. That technical foundation is what enables you to create content that drives measurable business impact through brand awareness and pipeline. We're trusted by 200+ world-class AI teams across robotics, logistics, automotive, insurance, gen AI and many others. If you want to create content at the intersection of cutting-edge AI applications and data infrastructure, this is your opportunity.

Job Responsibility:

  • Build a scalable content engine across key formats - video, webinars, podcasts, blogs - optimized for each stage of the buyer journey
  • Create sophisticated technical content that brings our AI data platform to life for executives and data practitioners
  • Collaborate with tech partners and leading AI teams to showcase cutting-edge use cases and real-world implementations
  • Develop customer stories and technical case studies
  • Create content for conferences, tradeshows, and executive roundtables
  • Partner with Encord Leadership and Product teams to align content strategy with business priorities
  • Pioneer new content formats that expand reach while generating measurable pipeline
  • Represent Encord at industry events and conferences (~2 weeks per quarter, Europe/USA)

Requirements:

  • Technical foundation - background in data ops, ML engineering, or data infrastructure from either a hands-on technical role or a commercial/GTM role
  • Examples of technical backgrounds: data engineer who built labeling pipelines, ML engineer who worked on MLOps workflows for model deployment/monitoring/fine-tuning, or data scientist who optimized training datasets
  • Examples of commercial backgrounds: solutions engineer, technical product manager or sales engineer at data/MLOps / annotation platforms
  • You can read a technical architecture diagram, understand model evaluation metrics, and discuss dataset quality, annotation workflows, and model accuracy with technical practitioners
  • Comfort creating or directing diverse content formats - whether that's recording technical demos, participating in webinars, or developing event presentations
  • Ability to translate complex technical concepts into compelling narratives for both practitioners and executives
  • Strategic commercial mindset - you understand which content bets drive pipeline and revenue
  • Hands-on operator who develops strategy but also executes
  • Comfortable with ambiguity and fast pace - you take initiative and adapt quickly
What we offer:
  • Competitive salary and equity in a hyper growth business
  • Strong in-person culture: most of our team is in the office 3+ days a week in our loft office in North Beach
  • 18 days annual leave a year + public holidays
  • Annual learning and development budget
  • Paid trips to visit prospects, attend conferences, host events across UK, Europe and US
  • Company lunches twice a week
  • Monthly socials & bi-annual off-sites

Additional Information:

Job Posted:
January 05, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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