We are a cutting-edge cybersecurity lab dedicated to addressing next-generation threats through advanced AI and machine learning. Our work spans multiple domains, including endpoint protection, cloud security, and AI-driven defense technologies. Our mission is to invent and implement breakthrough solutions that provide Huawei with a strategic edge in the global cyber defense landscape. By bridging research and engineering, our teams transform innovative concepts into real-world solutions that safeguard enterprises and critical infrastructure. We also maintain close collaborations with leading universities and international innovation hubs.
Role Overview
We are seeking a Senior Applied Machine Learning / AI Engineer with at least 5 years of hands-on experience in designing, developing, and deploying machine learning models, specifically for cybersecurity applications. This role combines applied ML engineering with innovation and research, requiring someone who can move seamlessly from proof-of-concept to production, and lead initiatives that drive our AI-driven security strategy.
Key Responsibilities
Lead the design, training, and deployment of advanced ML/DL models for cybersecurity use cases (malware detection, anomaly detection, network behavior analytics, adversarial ML defense, etc.)
Drive innovation by developing proof-of-concepts, exploring novel AI techniques, and translating research findings into practical, scalable solutions
Collaborate with cross-functional teams (security researchers, software engineers, product managers) to bring ML-driven features into production environments
Analyze large-scale, heterogeneous cybersecurity datasets (logs, network traffic, endpoint telemetry, threat intel)
Implement robust model monitoring, explainability, and optimization for real-world environments
Stay at the forefront of advances in AI, data science, and cybersecurity; identify emerging opportunities and mentor junior engineers/researchers
Represent the company in external collaborations, conferences, and innovation forums.
Requirements: BSc/MSc/PhD in Computer Science, Electrical/Computer Engineering, Data Science, or related field
5+ years of professional experience applying ML/AI in real-world projects (cybersecurity experience highly preferred)
Strong proficiency in Python and ML/DL frameworks (PyTorch, TensorFlow, Scikit-learn)
Proven experience taking ML models from research/prototype to production
Solid background in statistical modeling, anomaly detection, time-series, or NLP for security data
Familiarity with cybersecurity fundamentals: network protocols, threat types, SOC/incident response workflows, malware families, etc.
Experience with cloud environments (AWS, Azure, GCP) and data pipelines (Spark, Kafka, Airflow, etc.)
Strong problem-solving, innovation mindset, and ability to work in fast-paced R&D environments
Preferred / Nice-to-Have
Experience in adversarial machine learning or AI for threat simulation
Background in innovation projects (e.g., patents, published research, leading POCs)
Hands-on experience with graph neural networks, reinforcement learning, or generative AI in security contexts
Experience mentoring or leading small ML teams
Participation in academic collaborations or conference publications (Black Hat, IEEE, NeurIPS, etc.).
This position is open to all candidates.