Remote ML Engineer - Silicon Security & Threat Detection

Luxoft Poland; Województwo pomorskie; On-site; PLN 180,000 - 240,000; Full time

Job summary

Luxoft Poland is seeking an ML Engineer to lead model development and validation for a hardware-assisted security platform. You will focus on feature engineering, classifier development, and real-time inference integration within a global team.

The role emphasizes designing robust evaluation frameworks, handling CPU telemetry data, and optimizing models for efficient deployment on GPU/accelerators, while collaborating with systems engineers and lab teams.

Qualifications

• 4+ years of industry experience in applied machine learning or data science.
• Proficiency in Python and hands-on experience with ML frameworks (PyTorch, TensorFlow, or scikit-learn).
• Experience designing, training, and evaluating classification models.
• Experience with tabular/time-series/telemetry data and model evaluation metrics.

Responsibilities

• Design, train, and evaluate classifiers using CPU telemetry data.
• Perform feature engineering on hardware performance-counter data.
• Frame and label datasets, select features, and determine sampling/windowing parameters.
• Develop evaluation frameworks covering precision, recall, ROC-AUC, and latency.
• Analyze model behavior across workloads and threat variants; improve accuracy and robustness.
• Evaluate classification and anomaly-detection approaches for limited data scenarios.
• Optimize and quantize models for efficient inference on hardware accelerators.
• Export models for production and collaborate on runtime integration.

Skills

Python

Machine learning

Model evaluation

Feature engineering

Education

University degree in CS/EE/CE/Data Science/Math

Tools

PyTorch

TensorFlow

scikit-learn

ONNX

Job description

Luxoft Poland is seeking an ML Engineer to lead model development and validation for a hardware-assisted security platform. You will focus on feature engineering, classifier development, and real-time inference integration within a global team.

The role emphasizes designing robust evaluation frameworks, handling CPU telemetry data, and optimizing models for efficient deployment on GPU/accelerators, while collaborating with systems engineers and lab teams.