Staff Applied ML Engineer, FinCrime — Real-Time Risk AI

Wise; United Kingdom; Hybrid; GBP 145,000 - 182,000; Full time

Benefits offered by this job

RSUs

Wise Benefits

Job summary

Wise is seeking a Staff Applied ML Engineer to lead the next evolution of financial crime detection. You will own end‑to‑end ML architecture decisions, ship production neural models, and build scalable blueprints that span FinCrime domains.

You will collaborate with data scientists and platform engineers, operate with high autonomy, and mentor teams while delivering real-time, low-latency ML solutions across Wise’s global markets.

Qualifications

• Production experience shipping deep learning models at scale.
• Ability to make architecture-level decisions independently and explain tradeoffs.
• Experience designing ML systems with hard latency and throughput requirements.

Responsibilities

• Designing and shipping ML and deep learning models for financial crime detection at scale.
• Defining architecture strategy for applying modern ML to risk across model families and serving patterns.
• Building end-to-end pipeline patterns from experimentation to production deployment.
• Evaluating foundation models and embeddings for transaction representation across FinCrime domains.
• Collaborating with Data Science on model evaluation and experimental design.
• Mentoring engineers and data scientists on modern ML fundamentals and best practices.

Skills

Python

PyTorch

Distributed training

ML pipelines

Job description

Wise is seeking a Staff Applied ML Engineer to lead the next evolution of financial crime detection. You will own end‑to‑end ML architecture decisions, ship production neural models, and build scalable blueprints that span FinCrime domains.

You will collaborate with data scientists and platform engineers, operate with high autonomy, and mentor teams while delivering real-time, low-latency ML solutions across Wise’s global markets.