Machine Learning Engineer II

As a Machine Learning Engineer at Capital Group, you will create, research, implement, and maintain state‑of‑the‑art machine learning models, data pipelines, and analytical systems to significantly enhance our investment processes and outcomes. You will conduct applied research into financial modeling to help our investment professionals make better decisions and collaborate directly with senior investment professionals and technology associates to integrate ML techniques into our investment workflow.

Southern California Base Salary Range: $159,354–$254,966
• Seattle Base Salary Range: $159,354–$254,966

• Generous time‑away and health benefits from day one, with flexible work options.
• 2‑for‑1 matching gifts for charitable contributions and annual grants for chosen organizations.
• On‑demand professional development resources to hone and expand your skills.
• Competitive salary, bonuses, and a company‑funded retirement contribution that includes salary and variable pay.

• Design, research, build, deliver and operate machine learning systems, data pipelines, and financial models that demonstrably improve the efficiency and effectiveness of Capital Group’s investment process.
• Research, train, evaluate and deploy models for financial modeling and data analysis from inception through production and operation.
• Uphold high standards of quality, ensuring integrity in both form and function.
• Write clear, efficient, and high‑performance code.
• Collaborate effectively to support team strategy, contributing to decisions regarding modeling and technology.
• Proactively identify and tackle root causes of endemic modeling problems, collaborating with cross‑functional teams to implement sustainable solutions.
• Work with a sense of urgency, designing and building simple and pragmatic solutions to solve complex problems.

• 3+ years of experience with Python and SQL; strong object‑oriented or functional design skills and understanding of common design patterns.
• Demonstrated track record in one or more machine learning subfields relevant to financial modeling (time series analysis, quantitative modeling, optimization, anomaly detection, predictive analytics).
• Experience solving full‑stack machine learning problems from data collection and ETL development to model training, deployment, and operation, with real business impact in finance or investment management.
• Strong communicator capable of establishing and maintaining close working relationships with distributed team members and business partners.
• Solid computer science fundamentals, including data structures, algorithms, and complexity analysis.
• Knowledge of software engineering best practices (Agile, test‑driven development, unit testing, code reviews, design documentation).
• Track record of successfully delivering enterprise‑grade models into production.
• Experience with AWS services (S3, ECS & EKS, Lambda) preferred.

We are an equal‑opportunity employer. Our policies prohibit unlawful discrimination on the basis of race, religion, color, national origin, ancestry, sex (including gender and gender identity), pregnancy, childbirth and related medical conditions, age, physical or mental disability, medical condition, genetic information, marital status, sexual orientation, citizenship status, AIDS/HIV status, political activities or affiliations, military or veteran status, status as a victim of domestic violence, assault or stalking, or any other characteristic protected by federal, state or local law.