Senior Researcher, Machine Learning and System Security

Senior Researcher – Machine Learning & System Security

About the Role

We are seeking a Senior Researcher specialising in machine learning for platform and system security.

This role sits at the intersection of advanced machine learning, operating systems, computer architecture, embedded systems, and cybersecurity. The successful candidate will research and develop ML-based techniques for identifying, analysing, and mitigating security threats across complex computing platforms.

A strong foundation in modern machine learning is the primary requirement, combined with sufficient systems and security knowledge to work effectively on low-level and platform-focused research problems.

The position is full-time, permanent, and based on-site in Helsinki, Finland.

Key Responsibilities

• Research and develop machine learning techniques for platform, system, and device security.

• Apply neural networks, transformer-based models, probabilistic methods, and other modern ML approaches to practical security problems.

• Develop models for anomaly detection, threat identification, behavioural analysis, and security monitoring.

• Investigate the use of AI and machine learning for detecting vulnerabilities, attacks, malware, and abnormal system behaviour.

• Design and evaluate ML-based security solutions across operating systems, embedded platforms, and low-level software environments.

• Conduct experiments using real-world or representative security datasets and system telemetry.

• Analyse model performance, robustness, false-positive behaviour, and deployment constraints.

• Collaborate with researchers and engineers across machine learning, systems, cybersecurity, and hardware architecture.

• Build research prototypes and translate successful approaches into practical system implementations.

• Contribute to research publications, technical reports, internal demonstrations, and longer-term research initiatives.

Essential Requirements

• PhD or equivalent research-level expertise in Machine Learning, Computer Science, Applied Mathematics, Statistics, or a related technical discipline.

• Strong academic or practical background in probabilistic machine learning, statistics, or applied mathematics.

• Deep understanding of modern machine learning methods, including neural networks and transformer-based architectures.

• Hands-on experience applying AI or machine learning techniques to real-world problems.

• Strong programming and experimental development skills.

• Familiarity with computer architecture, operating systems, and systems-level concepts.

• Ability to design, implement, and evaluate machine learning experiments independently.

• Strong analytical and problem-solving skills.

• Ability to work effectively within multidisciplinary research and engineering teams.

• Strong written and spoken English.

• Interest in conducting applied research within an industrial environment.

Candidates completing a relevant PhD are also encouraged to apply. Applicants with significant industry experience may be considered where their practical expertise compensates for a different academic background.

Preferred Qualifications

• Experience developing low-level or operating-system-level software.

• Knowledge of hypervisors, virtualisation, kernels, firmware, or embedded systems.

• Strong programming skills in C, C++, Rust, or comparable systems languages.

• Understanding of CPU, memory, device, or hardware security architectures.

• Academic or practical experience in cybersecurity, cryptography, or secure systems.

• Experience with malware detection, threat intelligence, intrusion detection, or endpoint security.

• Knowledge of anomaly detection and behavioural security analytics.

• Experience researching or defending against software, firmware, or hardware attacks.

• Participation in capture-the-flag competitions, security research exercises, vulnerability analysis, or related technical challenges.

• Experience applying machine learning to security telemetry, system logs, binaries, network data, or low-level execution behaviour.

Candidate Profile

The successful candidate will have strong depth in machine learning together with an interest in understanding how modern computing systems behave at a low level.

You should be comfortable working across machine learning research and systems engineering, including situations where effective solutions require understanding both model behaviour and the underlying operating system or hardware environment.

The role is particularly suited to researchers interested in applying advanced AI techniques to practical problems in cybersecurity, platform protection, anomaly detection, and trustworthy computing.

Position Details

Location: Helsinki, Finland
Employment type: Permanent, full-time
Working arrangement: On-site