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range of industries within the field of technology
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Vice President of Machine Learning
Vice President of Machine Learning
We are seeking an exceptional Vice President of Machine Learning to lead its AI organization and define the next chapter of the company’s intelligence stack. This is a rare opportunity to join at a pivotal moment: We have the hardware, the platform, and the customers and now we need a world-class leader to build the models and AI systems that fully unlock their potential.
Reporting directly to the executive team, the VP of ML will own the company’s end-to-end AI strategy: from edge-optimized model architectures and developer tooling to frontier multi-modal systems for edge and on-premises deployment. The role combines deep technical leadership with cross-functional executive presence, and is expected to shape our AI roadmap through 2027 and beyond.
The successful candidate will lead and grow a high-caliber ML team, maintain our research culture, and serve as the external face of the company’s AI efforts — working alongside hardware, software, and go-to-market teams to ensure that AI is a genuine commercial differentiator for our customers.
Key Responsibilities
AI Strategy & Executive Leadership
- Define and own the company-wide AI strategy, ensuring alignment with hardware roadmaps, product vision, and go-to-market objectives.
- Serve as an AI thought leader internally and externally — representing the company at conferences, with customers, and with strategic partners.
- Work closely with the CEO, CTO, and other C-suite stakeholders to shape the long-term technology direction of the company.
- Translate research insights and market trends (edge inference, small model efficiency, vision-language models, test-time reasoning) into concrete product and platform bets.
Team Leadership & Organizational Development
- Lead, mentor, and grow a world-class ML team across research, model development, tooling, and deployment.
- Foster a culture of intellectual rigor, collaboration, and accountability — combining the best of academic and industry engineering norms.
- Drive hiring strategy: attract PhD-level researchers and senior ML engineers capable of working at the intersection of hardware and intelligence.
- Build clear career frameworks and development pathways for the ML organization.
Technical Execution
- Oversee the development of our optimized models and model serving optimization stack across CNNs, Vision Transformers, LLMs, and VLMs.
- Lead model compression, quantization, pruning, and co-design initiatives to achieve best-in-class performance/efficiency on Axelera hardware.
- Drive the creation of evaluation infrastructure and quality assurance pipelines for optimized models.
- Guide the design of multi-user serving frameworks for streaming Vision-Language Models and prepare for datacenter AI workloads.
- Oversee developer platform integrations (Hugging Face, PyTorch, and related ecosystems) that reduce customer friction and expand the addressable market.
Cross-functional Collaboration
- Partner with the Hardware and Software teams to align the AI roadmap with chip capabilities and software stack evolution.
- Work with Sales and Solutions Engineering to support strategic customer engagements, co-develop reference solutions, and identify AI-driven revenue opportunities.
- Support business development and fundraising activities where AI strategy and technical credibility are required.
Required
- PhD in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field from a leading research institution.
- 10+ years of experience in machine learning research or engineering, with at least 4–5 years in a senior technical leadership role (VP, Director, or equivalent) in an industry setting.
- Demonstrated track record of building and scaling high-performance ML teams, ideally in a fast-moving product company or deep-tech environment.
- Deep expertise in at least two of the following: model compression and efficient inference; large-scale training; vision-language models; data-centric AI.
- Experience bridging research and production: taking models from concept to deployed, customer-facing systems.
- Strong publication record or equivalent evidence of research leadership at top-tier venues (NeurIPS, ICML, ICLR, CVPR, OSDI, VLDB, SIGMOD, or similar).
- Proven ability to influence and communicate with executive stakeholders, customers, and the broader AI community.
Preferred
- Experience working at the intersection of hardware and machine learning — especially in on-device intelligence, inference optimization, or AI accelerator ecosystems.
- Prior experience co-founding or operating in a startup environment; comfort with ambiguity and rapid prioritization.
- Familiarity with edge AI deployment challenges: latency constraints, memory footprints, power budgets, and hardware-software co-design.
- Experience building developer platforms or ML toolchains used externally by customers or the open-source community.
- Network within the European and North American ML research and engineering communities.
This role is based in Zürich, Switzerland, with flexibility to engage with offices in Eindhoven (HQ), Leuven, Milan, Florence, and Bristol. Candidates willing to relocate to Zürich are strongly preferred.
- A defining leadership role at one of Europe’s most ambitious deep-tech companies, at the intersection of AI and silicon.
- Competitive executive compensation including base salary, performance bonus, and meaningful equity.
- A world-class team of 220+ colleagues — including 49+ PhDs — who combine scientific rigour with a genuine mission to advance AI for humanity.
- Full ownership of AI strategy at a company with $370M raised and a $100M+ business pipeline.
- An open, collaborative culture that prizes innovation, scientific integrity, and speed.
- Comprehensive benefits including pension plan, health insurance, and flexible working arrangements.
Apply Now
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