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

qarbonit; Wolfsburg; Hybrid; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

A leading tech firm seeks a Principal AI Scientist to lead research on autonomous AI systems. The ideal candidate should have a Ph.D. and extensive experience in AI R&D, particularly with transformer architectures and autonomous agents. This role offers flexible working arrangements and occasional travel to innovation hubs in Germany.

Qualifikationen

• 8–15 years of hands-on AI R&D experience.
• Proven record of publications in top-tier conferences.
• Experience in top-tier research environments.

Aufgaben

• Join a research program focused on autonomous AI systems.
• Develop AI architectures and enhance reasoning capabilities.
• Lead specialized teams in cutting-edge AI research.

Kenntnisse

Transformer Architectures

Deep understanding of transformer internals

Experience with Autonomous Agents

Strong background in Multimodal Models

Expertise in Graph Neural Networks

Understanding of HPC and GPU optimization

Proficiency in Python

Knowledge of C++

Ausbildung

Ph.D. in Computer Science

Tools

TensorFlow

PyTorch

Docker

Kubernetes

Jobbeschreibung

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).