Machine Learning Engineer
Build cutting-edge fraud detection systems using AI and big data analytics.
Apply NowAbout the Role
We’re seeking a talented Machine Learning Engineer to join our high-performance team. You will design and implement AI models that detect financial fraud in real-time by analyzing over 120 data points per transaction for 12,000+ global clients. You'll work with petabytes of transaction data to refine our machine learning pipeline and improve model accuracy.
Key Responsibilities
- Design and maintain fraud detection systems using TensorFlow/PyTorch
- Collaborate with security analysts on feature engineering for risk scoring
- Optimize ML models for low-latency execution in production systems
- Monitor model performance on 14 billion+ monthly transactions
What We're Looking For
Required Qualifications
- 5+ years ML model development experience
- PhD or MS in AI/ML with publication history
- Expert in Python/PyTorch/TensorFlow
- Fraud detection modeling experience
- Big data systems experience (Spark/Hadoop)
- Strong SQL and database optimization skills
We Also Want to See
Experience with AWS SageMaker
Familiarity with fintech security protocols
Publication in JMLR/NIPS proceedings
Experience with fraud modeling frameworks
We Offer
Competitive Base Salary
$170k - $230k annual
Performance Bonuses
Up to 30% of base salary
Equity Grants
Restricted Stock Units
Professional Growth
Annual $10k learning budget