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Research Team Leader LLM

Sii tra i primi a mandare la candidatura.
OPTIVEUM sp. z o.o.
Dubai
Remoto
USD 120.000 - 160.000
Sii tra i primi a mandare la candidatura.
7 giorni fa
Descrizione del lavoro

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 international Candidates with Project-based or Permanent job opportunities in a remote or office-based model.

Optiveum sp. z o.o. to firma rekrutacyjno-konsultingowa prowadzona na bazie naszego ponad 20-letniego doświadczenia na rynku usług HR i IT.

Pracujemy z klientami w Polsce i za granicą oferując międzynarodowym kandydatom pracę stałą lub projektową u Klientów w biurze lub w modelu zdalnym.

DANE FIRMY / COMPANY DATA

Optiveum Sp. z o.o.

ul. Tomasza Zana 43 lok. 2.1 20-601 Lublin

nr KRS : 0000834436, NIP 7010975729

Firma wpisana do Krajowego Rejestru Agencji Zatrudnienia pod numerem : 23910

Contact us at : info (at) optiveum.com

Research Team Leader – Reasoning Multimodal LLMs

Location : Remote but first 12 months willing to relocate 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 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.
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* Il benchmark retributivo si basa sugli obiettivi retributivi dei leader del mercato nei rispettivi settori. È pensato per orientare gli utenti Premium nella valutazione delle posizioni aperte e aiutarli a negoziare la propria retribuzione. Tale benchmark non è fornito direttamente dall'azienda, quindi la retribuzione effettiva potrà risultare anche notevolmente superiore o inferiore.

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