Machine Learning Engineer

CloudWalk, Inc.

Machine Learning Engineer focusing on building AI-driven security solutions at CloudWalk. Collaborate to deploy machine learning models that proactively detect and neutralize threats.

Posted 5/12/2026full-timeRemote • 🇧🇷 BrazilMid-LevelSeniorWebsite

About the role

Key responsibilities & impact

Engineer systems that anticipate and neutralize security threats before they reach infrastructure.
Design, train, and deploy machine learning models directly at the edge.
Bridge the gap between security intelligence and massive-scale data science.
Collaborate with red teamers and security engineers to turn attack data into proactive defense mechanisms.

Requirements

What you’ll need

Build edge intelligence. Design and train machine learning models focused on anomaly detection, bot mitigation, and zero-day intrusion detection.
Deploy at scale. Implement and optimize inference models to run efficiently at the edge, processing massive volumes of HTTP traffic with ultra-low latency.
Turn attacks into data. Work closely with our offensive security engineers to understand attack vectors, simulate realistic threats, and generate high-quality datasets for model training.
Automate the defense. Create robust data pipelines that continuously ingest traffic logs, monitor model performance, detect concept drift, and automate retraining based on the latest threat intelligence.

Benefits

Comp & perks

Fluency in Python and SQL, with deep proficiency in ML libraries like PyTorch, TensorFlow, or Scikit-Learn.
Experience deploying machine learning models into production, specifically dealing with high-throughput, low-latency requirements.
Strong understanding of web security, HTTP protocols, and common attack vectors (e.g., OWASP Top 10, L7 DDoS, credential stuffing).
Familiarity with edge computing platforms (Cloudflare, Fastly, AWS Edge) and CDN/WAF concepts.
Solid software engineering fundamentals. You code daily and can write production-ready services in Python, Rust, TypeScript, or similar languages to integrate your models with our stack.
Experience with cloud-based infrastructure (GCP/AWS) and managing large-scale datasets.
Experience with LLMs and Agents.
As a member of a fully remote and distributed team, you are expected to complete tasks autonomously, being highly collaborative and self-driven.
Ability to communicate effectively and debate complex technical concepts in both English and Portuguese.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learninganomaly detectionbot mitigationzero-day intrusion detectiondata pipelinesmodel traininginference modelsHTTP traffic processingconcept drift detectionautomated retraining

Soft Skills

collaborationcommunicationproblem-solvingproactive defense