“I can succeed as a Machine Learning Engineer at Capital Group”

We are seeking a Machine Learning Engineer to design, research, implement, deliver and operate predictive capabilities to demonstrably improve our investment process and outcomes. Capital Group will use these predictive capabilities to more efficiently and effectively make investment recommendations and decisions. This role will collaborate directly with senior investment professionals and other technology associates to create, research, implement, and operate state of the art predictive models, systems, and user experiences.

In this role you will work with a high performing team of applied scientists, machine learning engineers, and software development engineers. The ideal candidate for this role will be passionate about our mission and will drive for superior long-term investment results through the application of modern machine learning and software engineering methods.

“I am the person Capital Group is looking for.”

You will design, research, build, deliver and operate predictive models, systems and services which demonstrably improve the efficiency and effectiveness of CG’s investment decisions.
You successfully research, train, evaluate and deploy models from inception to completion, as well as operate them.
You bring a high level of craftsmanship to your work, ensuring integrity in both form and function.
You collaborate effectively to support team strategy, contributing to modeling and technology choices.
You work to identify and resolve the root causes of endemic modeling problems, and collaborate effectively with other teams to implement correct, long-term fixes.
You work with a sense of urgency, and design and build simple and pragmatic solutions which solve complex problems.

Required Experience

7+ years’ experience with at least one modern programming language such as Java, Python, C++ or C#. Strong OO or Functional design skills with understanding of common design patterns.
Outstanding communication skills, ability to establish and maintain a close working relationship with distributed team members and business partners.
Demonstrated track record in one or more machine learning subfield, such as forecasting, recommender systems, ranking and relevance, optimization, etc.
Experience solving “full stack” machine learning problems, from data collection to model training to deployment. Must have experience using machine learning or NLP to solve real business problems.
Strong computer science fundamentals including data structures, algorithms, and complexity analysis.
Knowledge of software engineering best practices (e.g. Agile software development, test-driven development, unit testing, code reviews, design documentation, etc)
Track record of successfully delivering enterprise-grade models into production

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Southern California Base Salary Range: $194,862-$311,779

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In addition to a highly competitive base salary, per plan guidelines, restrictions and vesting requirements, you also will be eligible for an individual annual performance bonus, plus Capital’s annual profitability bonus plus a retirement plan where Capital contributes 15% of your eligible earnings.

You can learn more about our compensation and benefits here.

Temporary positions in Canada and the United States are excluded from the above mentioned compensation and benefit plans.

We are an equal opportunity employer, which means we comply with all federal, state and local laws that prohibit discrimination when making all decisions about employment. As equal opportunity employers, 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.

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