Must have

• Python

• Machine learning

• PyTorch

• Deep learning

• English

Nice to have

• C

• C++

• PhD

• Degree

• Computer vision

Requirements description

Must have:

• Professional experience (at least 5 years) with Machine Learning / Deep Learning frameworks such as PyTorch, including specialized frameworks such as Hugging Face Transformers, MosaicML Composer, or similar
• Good knowledge of Machine Learning / Deep Learning theory and algorithms
• Strong programming skills in Python (C/C++ is a plus)
• Solid mathematical background
• Strong software engineering skills and algorithmic problem solving skills

Nice to have:

• MS or PhD degree in Computer Science or a related technical field (or equivalent experience)
• Ambition to become a Technical Leader in a field related to this role at TCL Research Europe
• Experience with Large Language Models and Multi-Modal LLMs is a strong plus
• Experience in Computer Vision is a plus
• Having several prestigious published papers is an additional plus
• Experience in deep neural networks inference, benchmarking and deployment process is an additional advantage (e.g., TensorRT-LLM, vLLM, SGLang, TFLite/LiteRT, etc.)

Offer description

TCL Research Europe is an R&D center focused on creating Artificial Intelligence and Cloud solutions for global products of TCL, a leading consumer electronics company with 120 000 employees across 78 countries, ranked n°2 worldwide TV producer.

We are looking for experienced Machine Learning Engineers to join us in order to build innovative Artificial Intelligence solutions. Successful candidates will conduct research and create prototypes and products in the field of AI models optimization and deployment.

We offer:

• Attractive salary adequate to skills and experience
• Work with the latest technologies on the market
• Private medical care
• Sports card
• Chinese and English language classes (upon your wish)
• Flexible working hours
• Non-corporate culture
• Friendly atmosphere

Your responsibilities

1. Implementing AI-based solutions using the best available tools and practices. Work on both on-device (TVs, smartphones, etc.) and cloud-based deployments.
2. Focusing on Large Models (LLMs, Multi-modal LLMs) with potential extension to Computer Vision problems and models
3. Conducting "practical research" and prototyping, searching for innovative methods and techniques that could be used to support AI models optimization and deployment
4. Reviewing, managing and designing code using SW Engineering good practices
5. Collaboration with other AI team members and stakeholders
6. Providing mentorship and guidance to AI engineers at varying seniority levels.