Technical Co-Founder: AI for Networking/Telecommunication (5G/6G)

Looking for a telecommunication/networking expert to help us implement the inference of AI models on programmable network nodes in different 5G/6G network settings: The workload for the target AI application will need to be distributed on a group of networking nodes (e.g., switches, SmartNICs, base stations), having heterogeneous hardware architecture.

## Tasks

• Define the industrial constraints on **B5G/6G** **KPIs,** such as **latency,** **resource footprint, bandwidth,** and for **different types of evolutionized networks** related to **RAN, WAN, LAN, MEC, etc**.
• Help to realize the customized implementation of AI models on a **distributed** group of **heterogeneous hardware** of **telecommunication devices (e.g., switches, SmartNICs, base stations).**
• Adjust aforementioned customized implementations for different **networking protocols** (e.g., **IPv6, Ethernet, TSN, HTTP, etc**).
• Help to design scalable **scheduling, orchestration,** and **dynamic resource allocation algorithms**, required to integrate aforementioned distributed AI implementations in various network settings.
• Lead the **technical validation and prototyping** with early adopters.
• Collaborate on grant writing, product roadmap, and tech strategy.
• Hire and mentor future engineers and researchers as the team grows.

## Requirements

• Based in **Germany**, with a **valid Niederlassungserlaubnis** or **German citizenship**.
• A **Master's or PhD** in **Computer Science**, **Electrical Engineering**, or related fields in **telecommunication and networking**.
• Strong understanding of the 5G/6G stack system hierarchy, from **radio access to packet processing**.
• Experience with **energy efficiency, sustainability**, **high-throughput**, and other impactful design techniques and goals.
• Experience with **distributed computing** and **orchestration techniques** in the **edge-to-cloud network** settings.
• Proven ability to build systems end-to-end: from prototype to deployable demo.
• Fluent in English; German is a bonus.
• A basic background in the following fields**:**

**Machine Learning:**

• Structure of DNNs, LLMs, or other AI models for embedded / edge devices.
• Quantization, pruning, knowledge distillation, or other optimization techniques for ML.

**Hardware Design:**

• Design and synthesis of AI accelerators for **FPGAs** or **custom ASICs**.
• Circuit-level optimization, High-Level Synthesis (HLS), or RTL design experience.

## Benefits

Non-paid job at the moment, equity share at the time of founding the company is considered.