Remote Senior ML Engineer for Malware Detection (Australia)

Jobgether; Australia; A distancia; AUD 140.000 - 190.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Fully remote work

Flexible hours

Paid vacation 24 days

Public holidays 10 days

Sick leave

Healthcare support

Wellness benefits

Learning & development

Innovation rewards

Dedicated GPU resources

Descripción de la vacante

Jobgether is partnering to fill a Senior ML Engineer - Malware Detection role, remotely from Australia. You will develop and deploy ML systems to detect malware at scale, collaborating with analysts and engineers. Expect work across classical ML, transformers, and AI-assisted workflows with dedicated GPU resources.

You will own the ML lifecycle from data to production, emphasizing rigorous evaluation, low false positives, and cost-aware deployment in large hosting environments.

Formación

• At least five years of production ML experience in adversarial domains such as cybersecurity or related areas.
• Transformer model training and fine-tuning including data prep, tokenization, LoRA/QLoRA or full fine-tuning.
• Strong Python, PyTorch, and Hugging Face skills; SQL for big data analysis.

Responsabilidades

• Lead development, evaluation, and deployment of ML systems to improve malware detection at scale.
• Develop models for malware classification, triage, and automated signature generation.
• Optimize inference throughput, latency, and resource usage for production deployment.
• Establish rigorous evaluation frameworks with time-based and campaign-based splits.
• Collaborate with analysts, detection engineers, and infrastructure teams.

Conocimientos

Production ML

Transformer models

Model evaluation

PyTorch

Python

Hugging Face

SQL

English writing

Herramientas

PyTorch

Hugging Face

llama.cpp

ONNX

Descripción del empleo

Jobgether is partnering to fill a Senior ML Engineer - Malware Detection role, remotely from Australia. You will develop and deploy ML systems to detect malware at scale, collaborating with analysts and engineers. Expect work across classical ML, transformers, and AI-assisted workflows with dedicated GPU resources.

You will own the ML lifecycle from data to production, emphasizing rigorous evaluation, low false positives, and cost-aware deployment in large hosting environments.