Founding Machine Learning Architect

Architect; Deutschland; Remote; EUR 100.000 - 130.000; Vollzeit

Zusammenfassung

A leading technology firm in Germany is seeking a world-class ML leader to architect and own their AI roadmap. In this foundational role, you will define the technical trajectory of the platform and lead a growing ML team in turning cutting-edge research into tools for chip engineers. The ideal candidate has deep expertise in ML for chip design and leadership experience in high-performance engineering teams. This role is key for innovation in chip design.

Qualifikationen

• Proven experience in architecting ML solutions for chip design.
• Experience leading high-performance engineering teams.

Aufgaben

• Contribute to building the ML roadmap for Architect.
• Architect and deploy novel agent-based systems.
• Lead and mentor a team of ML engineers.
• Interface with hardware engineers to identify bottlenecks.
• Stay ahead in state-of-the-art ML techniques.

Kenntnisse

Expertise in ML for chip design

Leadership experience

Cross-functional collaboration

Jobbeschreibung

We are looking for a world-class ML leader to architect and own our AI roadmap. This is a foundational role that will work closely with the founders to define the technical trajectory across our platform, including code generation, reinforcement learning, layout optimization etc. You'll lead a growing ML team and work cross-functionally to turn cutting-edge research into usable tools for chip engineers. You should bring deep expertise in ML for chip design, as well as leadership experience in high-performance engineering teams.

Responsibilities

• Contribute to building the ML roadmap and research strategy for Architect across RTL and PD domains.

• Architect and deploy novel agent-based systems, including fine-tuning models for RTL Code generation, physical design tasks automation and hardware problem reasoning.

• Lead, mentor, and scale a team of top-tier ML engineers. Guide research direction, implementation standards, and modeling infrastructure.

• Interface with hardware engineers to identify bottlenecks in chip design pipelines that ML can solve.

• Stay ahead of state-of-the-art techniques in ML4EDA, agent orchestration, and model compression/deployment.