Machine Learning Engineering Manager Senior

Capital Group•Los Angeles, CA

6d•$234,276 - $422,221

About The Position

As the Senior Manager for CoreML, you will lead an engineering organization responsible for designing, building, and operating AI/ML capabilities that shape how Capital Group’s investment professionals consume information, make decisions, and understand markets. In this role, you will guide a team that builds foundational platform components—LLM integrations, retrieval pipelines, evaluation frameworks, classification and summarization systems—and brings them to life in tools such as the Investments portal and cross-asset research applications. You will serve as both a strategic leader and a hands-on engineering coach—setting direction, guiding architectural choices, elevating engineering quality, and ensuring the team delivers production-ready solutions with reliability and rigor. You will partner closely with the Product team throughout the entire lifecycle: co-developing long-term vision, shaping the roadmap, exploring opportunities, rapidly validating ideas, and executing against shared goals. A core responsibility of this role is cultivating an environment of learning, curiosity, and technical depth. You will create the conditions for engineers and managers to explore new ideas, investigate emerging technologies, generate insights, and contribute to thought leadership across the firm. Your leadership will help ensure that CoreML is not only delivering solutions but also advancing understanding of what is possible with modern AI, as you drive transforming ambiguous problems into impactful capabilities that investors use every day.

Requirements

You have experience leading engineering teams that build and operate ML-driven products or platforms at scale.
You have strong partnership instincts with Product—comfortable shaping strategy, co-owning roadmaps, and aligning technical investment with business priorities.
You possess a deep understanding of software engineering fundamentals: OO and functional design, distributed systems, cloud architecture, testing, and operational excellence.
You have hands-on experience developing and/or integrating ML and LLM-based systems (RAG pipelines, embeddings, evaluation frameworks, orchestration, data integrations).
You are able to navigate ambiguity, connect details to high-level strategy, and synthesize complex information into actionable direction.
You have strong communication skills: clear, structured, concise, and effective across technical and business audiences.
You demonstrate curiosity, adaptability, and a willingness to evolve ideas based on new learnings or evidence.
You take a practical approach to problem solving—balancing ideal technical solutions with real-world constraints.

Nice To Haves

Ideally, you have exposure to investment workflows, financial data, or high-stakes, data-intensive enterprise environments.

Responsibilities

Vision, Strategy & Roadmap: You will define and evolve the long-term strategy for CoreML in partnership with Product—establishing a clear vision that connects investor needs, market trends, and technical opportunity. You will co-author the roadmap with Product, ensuring sequencing reflects both business value and platform scalability.
Execution & Delivery: You will lead engineering execution across distributed systems, ML pipelines, LLM-based architectures, and integration layers. You will translate high-level goals into clear and actionable technical plans, while ensuring solutions are reliable, maintainable, and production-ready. You will guide teams through design reviews, prototyping, experimentation, and operational rollout.
Collaboration & Stakeholder Engagement: You will partner closely with Product throughout discovery, shaping opportunities, testing assumptions, and evolving requirements. You will work cross-functionally with Architecture, Cloud, Security, and downstream engineering teams to ensure strong interfaces, predictable releases, and high system resilience. You will engage directly with investment professionals to validate ideas and understand real-world workflows.
Culture, Talent & Leadership: You will build a high-performing team grounded in strong engineering fundamentals, pragmatic problem solving, and excellent communication. You will foster a culture of research, experimentation, and ongoing learning—encouraging engineers to explore new methods, deepen expertise, and contribute to internal knowledge creation. You will develop and mentor engineering managers and senior ICs; set clear expectations and support their growth. You will encourage thoughtful debate, constructive feedback, openness to new ideas, and shared ownership of team outcomes.
Innovation & Thought Leadership: You will establish mechanisms for structured exploration: technical deep dives, reading groups, prototypes, internal papers, or proofs of concept. You will partner with Product to identify and evaluate emerging AI/ML capabilities, model families, and architectural patterns. You will ensure the team’s insights are shared broadly, influencing decision making across IG Tech and investment teams.