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Deep Learning Algorithm Intern at Imagen

Wrexham, Wales, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

20 Jun, 26

Salary

0.0

Posted On

22 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Deep Learning, Algorithm, Python, PyTorch, TensorFlow, Computer Vision

Industry

Software Development

Description

Imagen is looking for a highly motivated Algorithm Intern to join our cutting-edge AI team. This is a unique opportunity to work on real-world deep learning challenges, contribute to production-level systems, and collaborate with top-tier engineers and researchers. This is a full-time, 3-month internship, with the potential to transition into a full-time Algorithm Engineer position upon successful completion. Why Join Us? Work on cutting-edge AI technology used by real users Learn fast and gain real production experience Be part of a collaborative, high-impact team Opportunity to convert to a full-time role Responsibilities Design, implement, and improve deep learning models. Work on real-world AI problems using large-scale data. Collaborate closely with experienced engineers and researchers. Run experiments, analyze results, and optimize model performance. Take ownership of projects and drive them forward independently. Stay up to date with the latest trends in AI and deep learning. Requirements B.Sc. with honors from a leading university and Currently pursuing (or recently completed) an M.Sc. with a thesis. At least 6 months of hands-on Deep Learning experience (academic projects, thesis work, independent projects, or student roles). Background in working on research or data-driven projects. Strong drive, curiosity, and ability to deliver results. Solid programming skills (Python is a Must). Experience with DL frameworks (PyTorch / TensorFlow). Experience in Computer Vision (Advantege).

Responsibilities

The intern will be responsible for designing, implementing, and improving deep learning models while working on real-world AI problems using large-scale data. Key tasks include collaborating with engineers, running experiments, analyzing results, optimizing performance, and driving projects forward independently.