Principal Machine Learning Engineer – Remote AI Research Lead for High‑Performance Advertising Platforms

Why Join Disney Entertainment & ESPN Technology?

At Disney Entertainment & ESPN Technology, we are on a relentless quest to transform how the world experiences storytelling, sport, and news. Our portfolio spans iconic brands such as Disney+, Hulu, ESPN+, ABC News, and countless other digital properties that reach hundreds of millions of viewers daily. As a member of the Ad Platforms organization, you will help shape the future of advertising‑driven entertainment, powering the next generation of addressable, data‑rich, and AI‑enhanced experiences that delight audiences and create unprecedented value for advertisers.

Our culture is built on imagination, inclusion, and relentless curiosity. From the moment you log in remotely, you’ll be part of a collaborative ecosystem that encourages bold ideas, rapid experimentation, and continuous learning. Whether you’re pioneering new machine‑learning algorithms or mentoring a junior engineer, your work will have a direct impact on how stories are discovered, enjoyed, and monetized across the globe.

Position Overview

We are seeking a seasoned Principal Machine Learning Engineer – Research to lead the design, development, and deployment of cutting‑edge AI solutions for Disney’s high‑performance, micro‑service‑based Advertising Platform. In this role you will own the end‑to‑end lifecycle of predictive and optimization engines that power inventory forecasting, ad pacing, pricing, targeting, and delivery across Disney’s streaming and sports properties.

Key Responsibilities

• Strategic Innovation: Conceptualize and prototype novel AI/ML methodologies that address complex advertising challenges, such as real‑time inventory forecasting, dynamic pricing, and audience segmentation.
• Algorithm Architecture: Lead the design of robust, scalable algorithmic frameworks that integrate seamlessly with our distributed micro‑service ecosystem.
• End‑to‑End Model Development: Build, train, evaluate, and productionize models—from data ingestion pipelines to real‑time inference—ensuring low latency and high throughput.
• Large‑Scale Data Engineering: Engineer efficient data processing workflows using Spark, Flink, or similar technologies, and maintain feature stores that provide consistent, high‑quality inputs for ML models.
• Cross‑Functional Collaboration: Partner closely with product managers, ad operations, engineering leads, and analytics teams to translate business objectives into technical specifications.
• Mentorship & Leadership: Coach senior and junior engineers, fostering a culture of technical excellence, knowledge sharing, and continuous improvement.
• Performance Monitoring & Optimization: Implement rigorous A/B testing, monitoring, and feedback loops to continuously refine model performance and business impact.
• Research Dissemination: Publish findings internally, present at industry conferences, and contribute to patents that reinforce Disney’s position as a technology leader.

Essential Qualifications

• Education: Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, or a related quantitative discipline.
• Experience: Minimum of 10 years of professional software engineering experience, with at least 5 years focused on machine learning, deep learning, or data‑science research in a large‑scale production environment.
• Technical Mastery: Proven expertise in Python, Java, and/or Scala; hands‑on experience with TensorFlow, PyTorch, or similar deep‑learning frameworks; and strong command of large‑scale ML platforms such as Kubeflow, SageMaker, or internal ML pipelines.
• Mathematics & Statistics: Deep understanding of statistical modeling, optimization theory, and probabilistic inference as they apply to ad‑tech problems.
• System Design: Demonstrated ability to design, build, and operate high‑throughput, low‑latency micro‑service architectures that serve billions of ad requests daily.
• Collaboration Skills: Track record of influencing cross‑functional teams, translating technical concepts for product stakeholders, and leading technical discussions.
• Passion for Advertising: Strong desire to understand the ad business, translate research breakthroughs into product value, and drive measurable revenue outcomes.

Preferred (Nice‑to‑Have) Qualifications

• Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related field.
• Direct experience within the digital advertising or video‑streaming ecosystem.
• Hands‑on work with large language models (LLM) and generative AI for creative ad content generation.
• Expertise in forecasting algorithms, CTR/CVR prediction, and real‑time bidding strategies.
• Familiarity with MLOps tooling, feature stores, audience segmentation pipelines, and data versioning platforms.
• Experience building end‑to‑end pipelines that include model explainability, fairness, and compliance considerations.

Core Skills & Competencies for Success

• Algorithmic Thinking: Ability to break down complex ad‑tech problems into tractable mathematical formulations.
• Data Engineering Acumen: Proficiency with distributed data processing frameworks (e.g., Apache Spark, Flink) and data warehousing solutions.
• Software Engineering Excellence: Clean, test‑driven code, solid CI/CD practices, and a commitment to code review and documentation.
• Product Mindset: Understanding of key performance indicators (KPIs) such as fill‑rate, eCPM, and advertiser ROI, and the ability to align ML outcomes with business goals.
• Communication & Influence: Clear articulation of technical strategies to both technical and non‑technical audiences.
• Adaptability: Comfort operating in a fast‑moving environment where priorities shift quickly and innovation cycles are short.
• Leadership Presence: Proven capacity to inspire, mentor, and guide high‑performing technical teams.

Career Growth & Learning Opportunities

Disney Entertainment & ESPN Technology invests heavily in the professional development of its people. As a Principal Machine Learning Engineer, you will have access to:

• Global Learning Programs: Subscription to leading AI conferences (NeurIPS, ICML, KDD) and tuition reimbursement for advanced courses.
• Innovation Lab: Time‑boxed “Innovation Sprints” where you can experiment with emerging technologies such as generative AI, reinforcement learning, and causal inference.
• Mentorship Networks: Pairing with senior leaders across Disney’s broader technology ecosystem for cross‑disciplinary knowledge exchange.
• Leadership Pathways: Clear tracks toward senior technical leadership (Distinguished Engineer, VP of AI) or product‑centric roles (Director of Machine Learning Products).

Work Environment & Culture

Our remote‑first model empowers you to work from wherever you are most productive while still feeling fully integrated into Disney’s vibrant community. Highlights include:

• Collaborative Platforms: State‑of‑the‑art virtual collaboration tools, shared workspaces, and frequent “virtual coffee chats” that break down geographic silos.
• Diversity & Inclusion: Commitments to inclusive hiring, employee resource groups, and a culture where every perspective is valued.
• Well‑Being Benefits: Flexible work hours, mental‑health resources, and access to wellness programs.
• Creative Freedom: Autonomy to propose and prototype bold ideas, with executive sponsorship for high‑impact initiatives.

Compensation, Perks & Benefits (General Overview)

Disney offers a competitive total‑reward package designed to attract and retain top talent. While exact figures vary by location, the package typically includes:

• Base Salary: Market‑aligned compensation reflecting experience and expertise.
• Performance Bonus: Annual discretionary bonus tied to individual and company performance.
• Equity Awards: Long‑term incentive units (stock options or RSUs) that align your success with Disney’s growth.
• Health & Welfare: Comprehensive medical, dental, vision, and life insurance plans.
• Retirement Savings: 401(k) matching contributions and pension options where applicable.
• Paid Time Off: Generous vacation, holidays, and parental leave policies.
• Learning Stipends: Annual budgets for courses, certifications, and conference attendance.
• Employee Discounts: Access to Disney parks, entertainment, and retail discounts worldwide.

How to Apply

If you are excited about pushing the boundaries of AI in advertising, thrive in a collaborative, fast‑paced environment, and want to see your innovations reach millions of viewers around the planet, we want to hear from you. Submit your resume, a cover letter that highlights your most relevant achievements, and any portfolio or open‑source contributions that showcase your expertise.

Take the Next Step

Don’t miss the chance to be part of a legendary brand that blends imagination with technology. Apply today and help us write the next chapter of Disney’s advertising story.