Machine Learning Engineer II

Machine Learning Engineer

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. In this role, you will collaborate directly with senior investment professionals and fellow technology associates to enhance our investment process through the use of state‑of‑the‑art ML techniques.

You will work with a high‑performing team of applied scientists, machine learning engineers, and software development engineers that has delivered a number of AI/ML systems to production. We are seeking a candidate who has hands‑on experience architecting and delivering working systems and who is passionate about leveraging modern machine learning and software engineering innovations to produce superior long‑term investment outcomes.

• Design, research, build, deliver and operate machine learning systems, data pipelines, and financial models that demonstrably improve the efficiency and effectiveness of CG's investment process.
• Research, train, evaluate and deploy models for financial modeling and data analysis from inception to deployment and operation.
• Write clear, efficient, and performant code while upholding a high standard of quality and integrity.
• Collaborate effectively with 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 pragmatic solutions to solve complex problems.

• 3+ years of experience with Python and SQL. Strong object‑oriented or functional design skills with an understanding of common design patterns.
• Demonstrated track record in one or more machine learning subfields relevant to financial modeling, such as time series analysis, quantitative modeling, optimization, anomaly detection, or predictive analytics.
• Experience solving “full stack” machine learning problems, from data collection and ETL development to model training and deployment, and using machine learning to solve real business problems in finance or investment management.
• Strong communicator able to establish and maintain close working relationships with distributed team members and business partners.
• Strong 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, containers – ECS & EKS, Lambda) preferred.

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

In addition to a highly competitive base salary, you will be eligible for an individual annual performance bonus, Capital's annual profitability bonus, and a retirement plan where Capital contributes 15% of your eligible earnings.

Competitive salary, bonuses and benefits; company‑funded retirement contributions; generous time‑away and health benefits from day one; 2‑for‑1 matching gifts for charitable contributions; access to on‑demand professional development resources; flexible work options.

We are an equal opportunity employer. We comply with all federal, state and local laws that prohibit discrimination in all employment decisions. We prohibit unlawful discrimination on the basis of race, religion, color, national origin, ancestry, sex (including gender identity), pregnancy, childbirth, age, disability, genetic information, marital status, sexual orientation, citizenship status, HIV status, political activity, military or veteran status, status as a victim of domestic violence, assault or stalking, or any other characteristic protected by law.

We are committed to fostering a strong sense of belonging in a respectful workplace. We value your talents, traditions, and uniqueness and seek diverse perspectives, experiences, and backgrounds.