Senior ML Engineer - Hardware-Accelerated Threat Detection

Luxoft; Poland; On-site; PLN 180,000 - 360,000; Full time

Job summary

Luxoft, supporting AMD, seeks an accomplished ML lead to architect and drive a security-focused ML platform. You will guide model roadmaps, build scalable training pipelines, and push models from research to production across GPU/NPUs, while coordinating with hardware teams.

You will mentor engineers, optimize inference performance, and ensure robust, reproducible experimentation across threat taxonomy and behavioral detection. Prioritise collaboration with security vendors and internal partners.

Qualifications

• 7+ years of applied ML experience, including 3+ years in security, anomaly detection or hardware/systems ML.
• Expert-level proficiency in PyTorch or TensorFlow; strong Python; experience leading ML platform or infrastructure decisions. Demonstrated record of taking ML models from research to production deployment.
• Experience with model deployment on GPU, NPU or other specialized hardware accelerators.
• Ability to lead technical direction and influence cross-functional teams.

Responsibilities

• Define and lead the ML model roadmap, progressing from binary malware/benign classification through multi-class threat taxonomy to behavioral attack-pattern detection.
• Architect training pipelines that scale to a growing malware variant library with reproducible, versioned experiments; establish model quality gates for production promotion.
• Lead research into advanced detection techniques including behavioral sequence modeling and detection of novel, previously unseen threat categories.
• Optimize multi-class ML classifiers for NPU inference against throughput and latency requirements; collaborate with hardware teams on NPU capability requirements.
• Drive dataset strategy including coverage across threat categories, synthetic data generation and dataset quality standards.
• Mentor MTS ML engineers; lead model and code reviews; establish best practices for reproducibility, documentation and experimental rigor.

Skills

Applied ML

Security ML

Deep learning frameworks

Python

ML platform leadership

Hardware acceleration

Tools

PyTorch

TensorFlow

Python

GPU/NPUs

Job description

Luxoft, supporting AMD, seeks an accomplished ML lead to architect and drive a security-focused ML platform. You will guide model roadmaps, build scalable training pipelines, and push models from research to production across GPU/NPUs, while coordinating with hardware teams.

You will mentor engineers, optimize inference performance, and ensure robust, reproducible experimentation across threat taxonomy and behavioral detection. Prioritise collaboration with security vendors and internal partners.