Principal AI Scientist / Deep AI Research Engineer (Autonomous & Agentic Systems)

Who we are

At Qarbon IT , we bring together innovation, research, and engineering to create cutting-edge digital and intelligent systems.

We collaborate with global leaders on projects that explore the future of AI, autonomy, and cognitive computing.

Our goal is simple — to connect visionary minds with challenges that push the boundaries of what’s possible in machine intelligence.

We’re now looking for a Principal AI Scientist / Deep AI Research Engineer to join a forward-looking research program within Volkswagen Group Innovation , focused on autonomous and agentic AI systems that merge perception, reasoning, and real-world interaction.

🌍 Location / Work Mode

Flexible hybrid or fully remote collaboration (EU or global).

Occasional travel to Volkswagen Group Innovation hubs in Germany .

Contract Type

B2B

Long-term research partnership on  AI innovation and autonomy projects

🧠 Core Expertise

Transformer Architectures (LMMs & LLMs)

Deep understanding of transformer internals (attention mechanisms, positional encodings, parameter-efficient fine-tuning, model parallelization).

Experience developing or optimizing architectures comparable to GPT , Gemini , or DeepSeek .

Agentic AI Systems

Proven expertise in building autonomous agents capable of reasoning, planning, and multi-step decision-making.

Familiarity with AutoGPT , BabyAGI , LangGraph , or custom orchestrators.

Multimodal Models (VLAM / Vision-Language-Action Models)

Strong background in fusing visual, textual, and behavioral modalities for physical AI or robotics.

Experience with embodied AI datasets , reinforcement learning with human feedback (RLHF) , and simulation-to-real transfer .

Graph Neural Networks (GNNs)

Expertise in dynamic graph embeddings , message passing , and hybrid GNN-transformer architectures .

Application of GNNs in vehicle networks , sensor fusion , and perception pipelines .

Hardware-Aware AI Design

Understanding of HPC , GPU / TPU optimization , and AI model co-design with hardware constraints.

Familiarity with NVIDIA Jetson , Qualcomm AI Engine , or custom accelerator architectures is a strong plus.

⚙️ Tech Stack & Tools

Programming : Python, C++, Rust, CUDA, TensorFlow, PyTorch, JAX

Frameworks : HuggingFace, LangChain, DeepSpeed, Ray, OpenVINO

Domains : Reinforcement Learning, Self-supervised Learning, Cognitive Architectures, Robotics

Environments : Linux, ROS, Docker, Slurm, Kubernetes

🎓 Preferred Background

Ph.D. in Computer Science , Machine Learning , Robotics , or a related field.

8–15 years of hands-on AI R&D experience .

Proven record of publications (NeurIPS, ICML, CVPR, ICLR) or leadership in AI research teams .

Experience in top-tier research environments (e.g. Google DeepMind , OpenAI , Anthropic , Microsoft Research , Huawei , or similar).

💡 Soft Skills

Visionary thinker with strong technical and scientific intuition .

Capable of bridging theoretical research with applied engineering .

Collaborative leader with experience guiding small, specialized research teams.

Excellent communication in English (German is a plus).