3 Site Reliability Engineer Observability jobs

XTB is a global company from the financial industry, focusing on online trading of financial instruments. We are the largest FinTech in Poland and a leader in Central and Eastern Europe, and the range of our operations covers several countries, including Asia and South America. At XTB, we focus on the development of our employees, giving them opportunities to gain knowledge and skills in various fields, as well as offering a number of training and development programs. If you are looking for challenges and want to gain valuable experience in an international business environment, XTB is the right place for you. We are a certified Great Place to Work company. We are seeking a Senior Site Reliability Engineer to define and drive the reliability of XTB systems at the scale of millions of clients. In this role, you will strengthen SRE practices and shape the resilience of our entire technology stack through high-impact observability, ensuring our systems remain robust and scalable....

So, who are we? IG is a FTSE 100 fintech operating across five continents, serving over 1.3m customers and handling billions of dollars in transactions – built on scale, trust, and proof. We didn't pivot to innovation; it's how we've always operated. What that means for the people who work here is real: genuinely complex problems to solve, the technology and resources to tackle them properly, and the kind of scope that's rare in established businesses. The bar is high – bring a curious and forward-thinking mindset and we'll give you the platform to define what comes next. Join us at IG – the future gets built here. Your team The Platform SRE team is the engine of IG’s reliability programme. We sit within Infrastructure & Operations, working across IG’s hybrid estate of on-premises HashiCorp Nomad and AWS. We are not a reactive ops team. We build the platform, standards, and tooling that make reliability the default for every engineering...

We’re hiring an Machine Learning Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: you’ll design and operate data pipelines that feed models, and you’ll build the tooling that trains, deploys, monitors, and retrains them. You’ll work closely with research engineers and product teams, taking models from experimentation to production-grade systems with clear SLAs, reproducibility guarantees, and observable behaviour. This is not a research role; it is a hands-on engineering role focused on making ML systems work reliably at scale. What You’ll Work On Build and operate ML lifecycle infrastructure, including model packaging, deployment, versioning, rollback, and CI/CD. Implement model monitoring, experiment tracking, and reproducibility. Build and maintain reliable batch and near-real-time data and feature pipelines,...