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Senior Machine Learning Engineer | Irvine, CA

Job in Irvine, Orange County, California, 92713, USA
Listing for: NLP PEOPLE
Full Time position
Listed on 2026-05-24
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 201683 - 322693 USD Yearly USD 201683.00 322693.00 YEAR
Job Description & How to Apply Below

Senior Machine Learning Engineer

“I can be myself at work.”

You are more than a job title. We want you to feel comfortable doing great work and bringing your best, authentic self to everything you do. We value your talents, traditions, and uniqueness-and we’re committed to fostering a strong sense of belonging in a respectful workplace.

We intentionally seek diverse perspectives, experiences, and backgrounds, investing in a culture designed to celebrate differences. We believe that belonging leads to better outcomes and a stronger community of associates united by our mission. At Capital, we live our core values every day:
Integrity, Client Focus, Diverse Perspectives, Long‑Term Thinking, and Community.

“I can influence my income.”

You want to feel recognized r performance will be reviewed annually, and your compensation will be designed to motivate and reward the value that you provide. You’ll receive a competitive salary, bonuses and benefits. Your company‑funded retirement contribution will factor in salary and variable pay, including bonuses.

“I can lead a full life.”

You bring unique goals and interests to your job and your life. Whether you’re raising a family, you’re passionate about where you volunteer, or you want to explore different career paths, we’ll give you the resources that can set you up for success.

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

  • Enjoy generous time‑away and health benefits from day one, with the opportunity for flexible work options
  • Receive 2‑for‑1 matching gifts for your charitable contributions and the opportunity to secure annual grants for the organizations you love
  • Access on‑demand professional development resources that allow you to hone existing skills and learn new ones

You will join our Machine Learning Engineering team to build the next generation of AI products at Capital Group – including agentic systems, LLM‑powered workflows, and the platform that ensures they are safe, governed, and reliable in production.

You will operate at the intersection of production ML, GenAI and agentic workflows, and governed data infrastructure. In this high‑impact role, you will help define how enterprise‑grade AI systems are designed, deployed, and operated. You will work with a high degree of autonomy, mentor junior engineers, and drive engineering standards across projects built on Databricks, AWS, and agent‑based architectures.

What You Will Do AI Infrastructure & Production Systems
  • You architect and operate end‑to‑end production AI systems – designing, building, deploying, monitoring, and managing the full lifecycle of ML and GenAI workloads
  • You develop production‑grade cloud‑native environments optimized for AI/ML model training, serving, and orchestration
  • You establish and evangelize engineering standards, reference patterns, and reusable platform components for AI services across the firm
  • You design scalable inference pipelines, including retraining loops, drift detection, evaluation harnesses, and observability
Agentic Workflows & GenAI
  • You build agentic systems with multi‑step reasoning, orchestration, and tool/function calling, including MCP‑based integrations
  • You develop evaluation harnesses, traces, and replay tooling so agent behavior is observable and continuously improvable
  • You apply advanced prompt engineering, evaluation frameworks, guardrails, and human‑in‑the‑loop patterns to deliver reliable LLM‑powered features
  • You drive the agentic SDLC, defining how agents are designed, tested, evaluated, deployed, and monitored as first‑class production assets
Databricks & AWS Platform Engineering
  • You build solutions on Databricks (Unity Catalog, MLflow, Spark) and AWS, leveraging native AI capabilities for model training, serving, and governance
  • You use Infrastructure as Code to provision and manage cloud‑native, scalable, and secure environments
  • You integrate with vector stores, graph databases, Redis, Dynamo

    DB, and Elasti Cache to enable retrieval, memory, and state for AI applications
ML Engineering & Delivery
  • You build REST and streaming APIs to expose ML and agentic capabilities to downstream products and platforms
  • You apply advanced prompt…
Position Requirements
10+ Years work experience
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