Machine Learning Engineer

About the Role

At CloudWalk, our Security team doesn’t just react to threats; we engineer systems that anticipate and neutralize them before they ever reach our infrastructure. We are looking for a Machine Learning Engineer to build the intelligence layer of our edge defenses. You won’t just be tuning standard WAF rules or analyzing logs after the fact. You will design, train, and deploy machine learning models directly at the edge to detect anomalies, thwart intrusions, and block sophisticated attacks in real time. You will bridge the gap between security intelligence and massive-scale data science, turning raw network traffic into a proactive defense mechanism. You'll work alongside red teamers and security engineers, using their attack data to train models that make those exact attack classes obsolete. If you enjoy solving hard scaling problems, weaponizing AI for defense, and protecting billions of transactions, this role is for you.

What You'll Do 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. What We're Looking For 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. Bonus Points Direct experience with the Cloudflare ecosystem, specifically Cloudflare Workers, Cloudflare WAF, or Cloudflare Workers AI. Background in cybersecurity, such as building Intrusion Detection/Prevention Systems (IDS/IPS), threat hunting, or analyzing malware. Familiarity with payment industry security (PCI DSS, card tokenization, acquiring flows). Contributions to open-source security/ML tools, published security research, or CTF participation.