machine learning engineer for AI platforms

Global FinTech Talent is working with an early-stage AI company building intelligent products for real-world use. The company develops production-scale AI systems focused on reliability, persistent context, and long-running workflows.

• Build and operate production ML infrastructure;
• Design systems for model training, evaluation, deployment, inference, and experimentation;
• Optimise model serving for high-throughput, low-latency workloads;
• Develop reliable data, training, evaluation, and model-release pipelines;
• Build evaluation and benchmarking infrastructure to measure quality and detect regressions;
• Implement monitoring, tracing, observability, and alerting for AI/ML workloads;
• Improve reliability, scalability, latency, throughput, and cost;
• Identify bottlenecks across the ML stack and continuously improve performance;
• Create reusable platforms and tooling that help engineers and researchers ship faster.

• Strong software engineering fundamentals;
• Experience building ML infrastructure, platforms, or production machine learning systems;
• Hands-on experience with model deployment, inference, evaluation, or data pipelines;
• Strong understanding of distributed systems and reliability;
• Ability to write clean, maintainable, production-quality code;
• Comfort working in an ambitious, fast-moving environment;
• Strong sense of ownership and a bias towards continuous improvement.

• Fully remote across the European Union.