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Machine Learning Engineer II
Capital GroupMachine Learning Engineer at Capital Group developing models and data pipelines for better investment outcomes. Collaborating with investment professionals and technology associates to enhance investment processes.
Posted 6/3/2026full-timeSeattle • California, Washington • 🇺🇸 United StatesMid-LevelSenior💰 $159,354 - $254,966 per yearWebsite
Tech Stack
Tools & technologiesAWSPythonSQL
About the role
Key responsibilities & impact- Create, research, implement, and maintain state-of-the-art machine learning models and data pipelines
- Conduct applied research into financial modeling for investment professionals
- Collaborate with senior investment professionals and technology associates
- Uphold high standards of quality ensuring integrity in both form and function
- Collaborate effectively to contribute to decisions regarding modeling and technology
Requirements
What you’ll need- 3+ years of experience with Python and SQL
- Strong object-oriented or functional design skills
- Demonstrated track record in machine learning subfields relevant to financial modeling
- Experience solving full stack machine learning problems
- Strong computer science fundamentals (data structures, algorithms, complexity analysis)
- Knowledge of software engineering best practices
- Experience with AWS services (S3, containers – ECS & EKS, Lambda) preferred
Benefits
Comp & perks- Enjoy generous time-away and health benefits from day one
- Opportunity for flexible work options
- Access to on-demand professional development resources
- 2-for-1 matching gifts for charitable contributions
- Annual grants for organizations you love
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonSQLmachine learningfinancial modelingobject-oriented designfunctional designdata structuresalgorithmscomplexity analysissoftware engineering best practices
Soft Skills
collaborationcommunicationquality assurancedecision making