# Senior Machine Learning Engineer

**Company:** [OPSWAT](https://hotfix.jobs/companies/opswat)
**Location:** Timișoara, Romania
**Role:** ML Engineering
**Experience:** 5+ years
**Skills:** Python, scikit-learn, TensorFlow, PyTorch, AWS, MLOps, Machine Learning, Deep Learning, Feature Engineering, Model Evaluation, Data Preprocessing, Malware Analysis
**Posted:** 2026-08-06

> Leads the end-to-end development, deployment, and optimization of machine learning models for cybersecurity and malware detection. The role requires 5+ years of production machine learning experience, strong Python and ML framework expertise, and technical leadership across data, evaluation, and MLOps workflows.

## Job Description

## Responsibilities
- Lead the training, testing, and optimization of machine learning models for cybersecurity and malware, owning technical decisions end to end.
- Evaluate and select model architectures across classical machine learning and deep learning.
- Drive data exploration, feature engineering, and preprocessing across large structured and unstructured datasets.
- Design and own model evaluation pipelines, including validation strategies, benchmarking, and performance analysis.
- Partner with data engineers and threat researchers to improve data quality, feature sets, and model performance.
- Own the deployment, integration, and monitoring of machine learning models in production.
- Define and improve scalable machine learning workflows and model development lifecycle practices.
- Translate ambiguous business and product requirements into machine learning strategies and solutions.
- Mentor junior and mid-level engineers.
- Influence research and product direction for machine learning in critical-infrastructure security.

## Requirements
- Degree in Computer Science, Mathematics, Engineering, AI, or a related field; an advanced degree is a plus.
- 5+ years of hands-on machine learning experience, including a track record of shipping models to production.
- Deep understanding of machine learning algorithms, model training, evaluation techniques, and optimization methods.
- Strong Python skills and expertise with common machine learning libraries.
- Experience with data exploration, feature engineering, and real-world datasets at scale.
- Strong command of model evaluation metrics and validation strategies.
- Experience deploying and integrating machine learning models into production systems.
- Experience with cloud platforms, preferably AWS.
- Familiarity with MLOps practices and tools.
- Demonstrated technical leadership, including mentoring, architecture decisions, and setting standards.
- Experience in cybersecurity, malware analysis, or a related security domain is a strong plus.
- Strong problem-solving skills, attention to detail, and a bias toward experimentation.
- Excellent communication and cross-functional collaboration skills.

## Benefits
- The role focuses on machine learning for critical-infrastructure cybersecurity and malware protection.

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