Machine Learning Engineer, Platform & Production
Listed on 2026-06-27
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Software Development
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Cloud Engineer - Software, Software Architect
About You
We are looking for a passionate Staff Machine Learning Engineer to bridge the gap between cutting‑edge ML algorithm development and production‑grade, scalable software engineering for our search and personalization systems.
In this role, you will be the technical leader of our engineering rigor, design the core architecture, establish engineering best practices, create scalable MLOps pipelines, and design a codebase that allows the team to iterate, deploy, and quickly experiment in production. You will act as a force multiplier, elevating the software engineering capabilities of the entire ML team.
Responsibilities- Recommendation & Search Model Training Architecture:
Architect, build, and scale recommendation systems powering personalization and search experiences across our streaming platforms. - Codebase Architecture:
Design modular, scalable ML repositories built for rapid iteration, fast deployment, and production experimentation. - Engineering Excellence:
Establish coding standards, testing frameworks, code review workflows, and CI/CD pipelines using open‑source cloud technologies for ML and data science work streams. - Production Velocity:
Build infrastructure abstractions and components that allow seamless transition from model training to large‑scale serving. - Cross‑Functional Delivery:
Collaborate with other ML engineers, data scientists and product managers, to drive complex ML projects from conception to completion. - Strategic Planning:
Partner with product and engineering leadership to define, plan, and deliver against long‑term strategic goals. - Culture & Mentorship:
Mentor and influence engineers across organizations by demonstrating high‑quality work, advocating for the customer, and fostering an innovative, engineering‑driven culture.
- 8+ years of industry experience, with 4+ years as tech lead experience (preferred).
- Deep practical knowledge in designing scalable, production‑grade Search or Recommendation systems architecture.
- Knowledge of large‑scale distributed systems, architecture, APIs, and databases.
- Solid practical understanding in modern machine learning lifecycle, common pain‑points, and research and production environments.
- Staff level experience building production systems with expertise in Python/Java, containerization, and cloud platforms.
- Hands‑on experience with MLOps tools and frameworks (MLflow, Kubeflow, Sage Maker, etc.), or building internal systems.
- Familiarity with machine learning algorithms (in particular for recommender systems) is a strong plus.
Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law.
AccessibilityAccommodations
If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.
Compensation & BenefitsPay Range: $ - $ salary per year. Other rewards may include annual bonuses, short‑term and long‑term incentives, and program‑specific awards. Additional benefits include health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays, sick time, and vacation.
Fair Chance OrdinanceIf you’re a qualified candidate with an arrest or conviction record, please know that your application will be considered in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
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