Senior Researcher, Machine Learning and System Security
Huawei Finland R&D Helsinki, Uusimaa, Finland
Telecommunications · 10,001+ employees
About the role
The researcher will specialize in machine learning for platform security, focusing on anomaly detection and threat intelligence. They will work on integrating these security decisions into terminal devices while maintaining performance and accuracy.
What they look for
Requirements
Candidates should hold a PhD or have equivalent industry experience with a strong background in probabilistic machine learning and statistics. Proficiency in low-level programming, computer architecture, and security concepts is highly preferred.
Full description
Helsinki System Security Lab (HSSL) – Senior Researcher, Machine Learning and System Security
With recent developments in Agentic AI, the impressive capabilities of large language models and the widespread application of AI-based services, products and tools, the security architecture of (consumer) computing devices is adapting to new concepts of computing – among others the transition from application-based to agentic devices, heterogeneous architectures with security features distributed between accelerators and CPUs as well as new access control demands related to balancing agentic capabilities against protection a devices against attacks. Additionally, machine learning models can likely also be leveraged as a framework for security decisions related to anomaly detection, threat intelligence (APT) – even access control - if the logic can be synthetized to setups that are small and fast enough to be used e.g., locally on terminal devices without harmful loss of accuracy.
We are looking to complement our team with a researcher whose main direction will be specializing in machine learning for platform security. Preferably the candidate has a solid background in both machine learning techniques and technology (neural networks, inference architectures, including transformers) and the application of such, as well as skills and experience needed for platform security, i.e., a solid understanding of security concepts and cryptography, computer hardware and architecture (OSs) as well as low-level/embedded programming. For this candidate, a deep understanding of ML however takes priority. We are looking for PhD-level candidates (fresh or soon-to-be graduates), or potentially candidates with a lower education level, but solid industry experience in the fields presented. The position is full-time, permanent, on-site in Helsinki, Finland
We are looking for:
- PhD-level candidates
- Strong educational background in probabilistic machine learning, statistics, applied mathematics
- Hands-on experience in applying AI/ML to real-world use cases
- Familiarity with computing architecture and operating system internals
- Sufficient skills to work and interact in English
- Good team-working skills
- Candidates with interest to conduct research in an industrial environment
The following we count as advantage:
- Solid experience with low-level, OS-like software (hypervisors), hardware architecture
using programming languages such as C, C++ or Rust.
- Education / experience / coursework in security-related fields such as cryptography, cybersecurity, virus protection / threat intelligence, anomaly detection, attacks (CTF, ..)
Location: This position is located at our R&D office in Ruoholahti, Helsinki, Finland. The role requires full-time onsite work from our Helsinki office.
Employement type: This is a full‑time employee position.
Helsinki Systems Security Laboratory in Huawei Finland (HSSL) drives renewal and mastery in the field of platform / device related security technologies for consumer devices such as mobile phones and PCs. Our topical expertise lies in hardware-assisted memory protection, trustworthy execution (processor isolation primitives, hypervisor, TEE, kernel hardening), as well as functionality like device key management, attestation and integrity. We are also making inroads in the areas of security testing and AI protection on terminal devices.
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