Data Scientist AI Machine Learning, Graduate, Internship, Student Placement

Id Job: 3172354

🏒 On-site
πŸ’Ό AI Top Talents Ltd
πŸ“ Bristol, England
πŸ•’ Today
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Job Description

Are you interested in joining a deep tech company working with leading Aerospace, Defence and Automotive companies like Airbus, GKN, BAE Systems, Nissan Motors etc.?

Are you interested in being part of a young and fun-loving team environment developing cutting-edge AI technology to solve real industrial problems?

If the above questions excite you, this company could be right for you!

We are looking for an engineer passionate about problem-solving. Your design, code, and natural smartness will contribute to solving some of the most complex industrial challenges. You will be involved in shaping our AI products and lead mission-critical projects early in your career.

Key Job Responsibilities

  • Develop supervised and unsupervised machine learning models, for example, XGBoost, KNN etc.
  • Develop Explainable AI modules to present machine learning results to end users
  • Implement multi-objective optimisation algorithms using the trained machine learning (surrogate) models
  • Develop uncertainty quantification modules to highlight the uncertainty in the prediction
  • Develop deep learning models using Neural Networks, e.g. Auto Encoders, Generative Adversarial Networks (GANs), Federated Learning etc.
  • Implement cutting-edge AI algorithms from published scientific documents
  • Write technical articles/blogs on industrial use cases.

Qualifications

  • Studied Data science, Artificial Intelligence, Machine Learning etc.
  • Mastery of Python programming language
  • Strong written and verbal communication skills
  • Basic working experience/knowledge in Unix/Linux environment
  • Basic understanding of containerised applications, for example, Docker
  • Basic knowledge of GPU-based highly parallel software development

Job Types: Full-time, Permanent, Graduate, Internship

Benefits:

  • Casual dress
  • Company events
  • Company pension
  • Referral programme
  • Work from home

Schedule:

  • Monday to Friday

Education:

  • Master's (preferred)

Work Location: Hybrid remote in Bristol

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