AI Engineering Services (Mid-Senior)
Timișoara, Romania
3 zile în urmă
source : Just Join IT

AI (junior)

Machine Learning (junior)

About Pearson

Did you know Pearson is one of the 10 most innovative education companies of 2022?

At Pearson, we add life to a lifetime of learning so everyone can realize the life they imagine. We do this by creating vibrant and enriching learning experiences designed for real-life impact.

We’re on a journey to be 100% digital to ensure we can deliver direct to consumers everywhere. This has only been accelerated by COVID-19.

To meet the changing needs of the global population we have developed a new strategy with ambitious targets. Our Purpose Add Life to a Lifetime of Learning .

At Pearson, we are focused on delivering the best products and outcomes to more people than ever before by leveraging technology, such as the Pearson Learning Platform

We are currently looking for independent contractors, service providers within AI Engineering filed

Services : AI Engineering (Mid-Senior)

Rates : 100-160 PLN Net + VAT, (depending on service level)

Contract type : B2B

Location : Independent - remote or optionally, Pearson Poznań office

Business capabilities required

  • Python and / or GO
  • Code review, multi-stage testing, CI / CD, etc.
  • DevOps or MLOps : building pipelines, CI / CD systems, automation, etc.
  • AI / ML frameworks and tools, e.g., TensorFlow, PyTorch, etc.
  • Linux or Unix
  • Working in a diverse, remote, asynchronous team
  • Collaborative communication, both in written and spoken English
  • Natural business desire for continuous learning, within AI / ML and programming skills
  • Services :

  • R&D on systems used in multiple e-learning platforms and mobile apps across Pearson
  • Occasional work with business on spikes and proof-of-concepts
  • Building and Implementation from scratch or development of existing automation pipelines of Pearson’s AI services and R&D tools
  • Architecture design & development of backend services (microservices)
  • High Quality of delivered implementation (peer code reviews, improving CI / CD pipelines, automated tests, etc)
  • Knowledge exchange, best practice
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