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About the Role
Decision Science colleagues will serve as a key member of the Credit and Fraud Risk organization, developing analyses, models, and algorithms that power customers’ digital experiences. This team manages enterprise risks across consumer and commercial businesses globally, developing data capabilities, decision-making frameworks, machine learning models, and customer servicing strategies.
Responsibilities
- Own the design, implementation, and optimization of sophisticated machine learning algorithms in modern C++, from mathematical formulations through production implementation.
- Translate mathematical and statistical concepts into efficient algorithms and production-quality C++ implementations.
- Develop a deep understanding of existing algorithms and improve their mathematical formulation, computational design, data structures, numerical behavior, efficiency, and scalability.
- Profile and optimize CPU implementations using algorithmic improvements, parallelism, multithreading, vectorization, memory/cache optimization, and other high-performance computing techniques.
- Design and implement CUDA C/C++ solutions to accelerate computationally intensive ML algorithms on NVIDIA GPUs.
- Optimize GPU computation, memory access, synchronization, data movement, and hardware utilization.
- Architect single- and multi-GPU execution, addressing workload decomposition, GPU communication, synchronization, memory management, and scalability.
- Build and optimize GPU-enabled workloads on Google Cloud Platform (GCP).
- Establish rigorous validation, numerical correctness, CPU/GPU equivalence, benchmarking, and performance-regression methodologies.
- Integrate high-performance C++/CUDA implementations with Python-based ML environments and collaborate with partner teams and downstream users.
Requirements
- PhDs in a quantitative field (Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Physics, Statistics, etc.) with hands-on experience developing sophisticated machine learning algorithms and techniques.
- Contribution to open-source project in C++/CUDA is a significant plus.
- Strong foundation in mathematics, statistics, optimization, and machine learning.
- Deep expertise in modern C++, algorithms, and data structures.
- Demonstrated experience implementing and optimizing complex mathematical, numerical, or machine learning algorithms.
- Ability to work across mathematical formulation, algorithm design, and software implementation.
- Strong understanding of computational complexity and performance engineering, including memory management and locality, multithreading, concurrency, vectorization, profiling, and benchmarking.
- Strong hands-on experience with CUDA C/C++ and NVIDIA GPUs, including development, debugging, profiling, and optimization of GPU software.
- Strong understanding of CPU/GPU parallel algorithm design, including memory hierarchy, data movement, synchronization, workload decomposition, and efficient mapping of algorithms onto GPU hardware.
- Experience with multi-GPU computing on the cloud, including workload distribution, communication, synchronization, memory management, and scaling computational workloads across GPUs.
- Strong proficiency in Python and experience integrating high-performance C++/CUDA components into production machine learning or computational systems.
- Expertise in an analytical language (Python, R or the equivalent), and experience with databases (Hive, SQL, or the equivalent).
- Experience with data visualization is a plus.
- Demonstrated ability to frame business problems into mathematical programming problems and leverage external thinking and tools to engineer a solution and deliver business insights.
- Ability to work effectively in a team environment.
- Independent thinker who’s organized, has great attention to detail, and can multi-task.
- Strong communication skills.
- Strong team player with a demonstrated ability to develop team members and create highly effective and results-driven culture.
- Strong relationship management and proven track record of positively collaborating and partnering with stakeholders.
- Ability to learn quickly and work independently with sophisticated, unstructured initiatives.
- Ability to integrate with cross-functional business partners worldwide.
- Proficient in presentation tools, including Excel and PowerPoint.
Skills
- C++
- Machine Learning
- CUDA C/C++
- NVIDIA GPUs
- Google Cloud Platform (GCP)
- Python
- R
- Hive
- SQL
- Excel
- PowerPoint
Work Type
- Hybrid
- Onsite
- Virtual
Education Level
- PhD
Benefits
- Competitive base salaries
- Bonus incentives
- Support for financial-well-being and retirement
- Comprehensive medical, dental, vision, life insurance, and disability benefits
- Flexible working model
- Generous paid parental leave policies
- Free access to global on-site wellness centers
- Free and confidential counseling support through our Healthy Minds program
- Career development and training opportunities
About the Company
- At American Express, our culture is built on a 175-year history of innovation, shared values, and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues.
- We operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.
- As part of Team Amex, you’ll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career.
- Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.
Equal Opportunity
- Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.