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Research Team Leader LLM
Job summary
A leading recruitment firm seeks a Research Team Leader for a major AI initiative focused on developing multimodal LLMs. This impactful role involves leading a team, shaping research strategies, and collaborating with global tech hubs, ideal for experienced AI/ML professionals.
Benefits
Qualifications
- At least 5 years of experience in AI/ML research.
- Strong expertise in deep learning architectures.
- Hands-on experience with modern deep learning frameworks.
Responsibilities
- Lead the research strategy for reasoning-capable multimodal LLMs.
- Manage a team of researchers and applied scientists.
- Collaborate with international research groups.
Skills
Education
Tools
Optiveum is a recruitment and consulting company created based on our 20-plus years of experience in HR &IT services.
We work for Clients located in Poland and abroad providing our local and internationalCandidates with Project-based or Permanent job opportunities in a remote or office-based model.
DANE FIRMY / COMPANY DATA
nr KRS : 0000834436, NIP 7010975729
Contact us at : info (at) optiveum.com
Research Team Leader – Reasoning Multimodal LLMs
Location : Remote but first 12 months willing torelocate temporarily to Shenzhen, China
The 12+ months in Shenzhen assignment is fully covered by the client : flights, accommodation, etc.
After this time, the candidate can work remotely from any European country.
Our client is a global consumer electronics leader with 120,000 employees across 78 countries and ranks as the #2 TV brand worldwide. Their portfolio includes display technologies, mobile and wearable devices, smart appliances, and renewable energy solutions.
They are launching a major AI initiative to develop advanced Reasoning Multimodal Large Language Models (LLMs) —capable of processing and reasoning across text, images, and audio for real-world industrial applications.
They are now seeking a Research Team Leaders to shape the research agenda, lead a high-caliber team, and collaborate closely with business units, particularly in display and photovoltaic manufacturing where multimodal data is key.
Key Responsibilities
- Lead the research strategy for reasoning-capable multimodal LLMs (text, vision, speech).
- Manage a team of researchers and applied scientists; provide mentorship and technical guidance.
- Oversee model pre-training, fine-tuning, synthetic data generation, RAG (Retrieval-Augmented Generation), Chain-of-Thought reasoning, and agentic workflow development.
- Bridge fundamental research and real-world product applications.
- Collaborate with international research groups, including strategic partners such as the Alibaba Qwen LLM team.
- Stay at the forefront of advances in deep learning, LLMs, and multimodal AI.
What We Offer
- Leadership role in a high-impact, greenfield AI research project.
- Attractive compensation based on experience and qualifications.
- Opportunity for accelerated professional development.
- Exposure to cutting-edge technology and collaboration with globally recognized AI teams.
- Potential for temporary assignments in Shenzhen, China, one of the world’s leading tech innovation hubs.
Candidate Profile
Must-have :
- At least 5 years of experience in AI / ML research, including leadership responsibilities.
- Strong expertise in deep learning and architectures such as Transformers, CLIP, or SAM.
- Hands-on experience with modern deep learning frameworks, preferably PyTorch.
- MSc or PhD in Computer Science, Mathematics, or a related technical field.
- Excellent command of English and a strong sense of ownership and collaboration.
Nice-to-have :
- Willingness to work on-site in Shenzhen for strategic collaboration phases.
- Track record of mentoring or growing research teams.
- Publications in top-tier conferences (e.g., NeurIPS, ICLR, ICML, CVPR, ACL).
- Success in technical competitions in AI, mathematics, or algorithm design.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.