Machine Learning Engineer

About This Role
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 You Need To Succeed
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.
Nice to Have
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.
The Future We See
At CloudWalk, we envision a future where AI empowers every field to reach new heights:
People teams leveraging AI to transform talent acquisition and employee development.
Marketing professionals creating data-driven, AI-powered campaign strategies.
Customer Success teams enhancing client experiences with intelligent solutions.
Risk analysts combining human expertise with AI to navigate complexities.
Designers collaborating with AI to push creative boundaries.
Join us at CloudWalk, where we're not just engineering solutions; we're building a smarter, AI-driven future for payments—together.

Work arrangement
Yes