Staff Machine Learning Engineer

Deine Rolle im Team

Unsere Erwartungen an dich

Qualifikationen

• Technical Leadership Without Authority: Proven ability to drive technical decisions across teams you don't manage-through clear writing, credibility, and the ability to synthesize competing perspectives into a coherent path forward.
• Deep Classical & Applied ML Mastery: Expert-level command of classical ML (XGBoost, LightGBM, calibration, cost-sensitive learning) with the judgment to know when-and when not-to reach for more complex approaches.
• You've operated beyond standard accuracy metrics and can design evaluation frameworks appropriate to the problem.
• You've owned reliability, SLAs, and incident response for ML systems, and you've built MLOps tooling-not just consumed it.
• Software Engineering Excellence: You write and review code at a senior+ level in Python, hold the team to high standards for testability and maintainability, and can credibly engage in systems design discussions with Principal and Staff engineers across Data and Platform.
• Strategic Thinking & Business Acumen: You connect technical decisions to business outcomes-approval rate improvements to revenue, latency reductions to conversion, model drift to operational risk.
• You communicate clearly with non-technical stakeholders and can translate ambiguous business goals into concrete ML problems.
• Payments Domain Depth: Strong understanding of the card payment lifecycle, issuer behavior, authorization codes, retry logic, network rules, and 3DS.
• You use domain knowledge to inform feature design, model architecture, and experimentation strategy-not just as background context.

Erfahrung

• ML Architecture at Scale: Demonstrated experience designing and shipping ML systems that serve multiple products or teams-not just models, but the platforms, contracts, and abstractions that make ML reusable and reliable at scale.
• Production ML Engineering: Extensive experience taking models from experimentation to high-throughput, low-latency production environments.
• Cloud Infrastructure Mastery: Deep experience designing and owning ML infrastructure on AWS or GCP at scale, including infrastructure-as-code, cost management, and the ability to make build-vs-buy decisions on platform components.

Unser Angebot