Product Ops Intern: AI‑Driven Ops (London)

Product Ops Intern: AI‑Driven Ops (London)

Full-Time 70000 - 90000 £ / year (est.) No working from home possible
Vega

At a Glance

  • Tasks: Help build and operate AI-driven product workflows while collaborating with various teams.
  • Company: Exciting early-stage startup in London focused on innovative AI solutions.
  • Benefits: Gain hands-on experience, mentorship, and exposure to cutting-edge technology.
  • Other info: Perfect opportunity for early-career professionals looking to make an impact.
  • Why this job: Shape operational systems and contribute to high-growth initiatives in a dynamic environment.
  • Qualifications: Passion for AI and eagerness to learn in a fast-paced setting.

The predicted salary is between 70000 - 90000 £ per year.

Vega is an early-stage startup in London seeking a hands-on early-career professional to help build and operate AI-enabled product workflows.

You’ll work with Product, Engineering, and leadership to own execution, design scalable internal processes, and drive client automation across the platform.

You’ll gain exposure to AI-native product development and have the chance to shape Vega’s operational systems while contributing to high-growth initiatives in a collaborative, fast-paced environment.

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Product Ops Intern: AI‑Driven Ops (London) employer: Vega

Vega is an exceptional employer for those looking to kickstart their career in a dynamic and innovative environment. As a Product Ops Intern, you'll not only gain invaluable experience in AI-driven product workflows but also enjoy a collaborative work culture that fosters creativity and growth. With opportunities to shape operational systems and contribute to high-growth initiatives, Vega offers a unique chance to be part of a forward-thinking startup in the heart of London.

Vega

Contact Details:

Vega Recruitment Team

We think you need these skills to ace Product Ops Intern: AI‑Driven Ops (London)

Python
Communication Skills
SQL
Problem-Solving Skills
Data Engineering
ETL/ELT Processes
Data Pipeline Development