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Senior Machine Learning Engineer
Senior Machine Learning EngineerDisney Entertainment and ESPN Product & Technology • Glendale, California, United States
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Disney Entertainment and ESPN Product & Technology • Glendale, California, United States
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  • [job_card.full_time]
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Job Summary :

The Ad Platform Engineering organization within Disney Entertainment and ESPN Product & Technology is responsible for building, enhancing, and operating a high-performance, distributed, microservice-based digital advertising platform. This platform powers billions of real-time ad decisions daily across Disney’s video-on-demand and live TV properties, including Hulu, Disney+, ESPN, and more.

Within Ad Platform Engineering, the Programmatic teams build and maintain Disney’s programmatic advertising suite of products and services that comprise Disney's Real-time Ad Exchange (DRAX). DRAX is an award-winning, proprietary supply-side platform (SSP) that enables programmatic deal configuration and integrates demand from multiple third-party sources into Disney’s ad server in real time.

As a Senior Machine Learning Engineer, you will design, build, and operate production machine learning systems that directly impact revenue, efficiency, and viewer experience at global scale. This is a hands-on, production-focused role, ideal for an experienced ML engineer who enjoys owning complex systems end-to-end, partnering closely with product and engineering teams, and delivering measurable impact in low-latency, high-throughput environments operating at billion-request-per-day scale.

This role is not research-only. Success is measured by production outcomes, system reliability, model performance, and continuous iteration based on data and feedback.

Daily, you should bring :

  • Strong technical ownership and accountability for production ML systems
  • Effective collaboration and communication across engineering, product, and data partners
  • Comfort operating in ambiguity and translating loosely defined problems into scalable solutions
  • A continuous improvement mindset with attention to performance, reliability, and cost
  • The ability to define and use technical and operational metrics to measure system and model health

Responsibilities :

  • Apply modern machine learning techniques to advertising use cases such as inventory forecasting, pricing, targeting, and efficient ad delivery
  • Design, implement, and iterate on ML solutions from experimentation through production deployment and ongoing optimization
  • Build and scale ML architectures that balance model quality, latency, throughput, reliability, and cost
  • Design and maintain feature pipelines and feature stores supporting both real-time inference and offline training
  • Own major components of the model lifecycle, including experimentation, validation, deployment, monitoring, and iteration
  • Analyze experimental results and partner with product and engineering stakeholders to support data-informed decisions
  • Ensure models are observable, debuggable, and explainable in production environments
  • Implement monitoring for model performance, drift, bias, and overall system health
  • Contribute to engineering excellence through high-quality code, sound system design, and operational best practices
  • Provide technical guidance through code reviews, design discussions, and knowledge sharing
  • Basic Qualifications :

  • Bachelor's degree in Computer science or related field of study
  • 5+ years of software engineering experience
  • Minimum 3 years of hands-on experience developing and deploying machine learning systems in production
  • Strong knowledge of machine learning fundamentals, mathematics, and statistics
  • Experience operating ML systems in low-latency, high-throughput environments
  • Strong communication and collaboration skills with both technical and non-technical partners
  • Solid foundations in algorithms, data structures, and numerical optimization
  • Proficiency in Python (primary), with experience in Java and SQL
  • Experience with modern ML frameworks and tooling such as TensorFlow, PyTorch, and Hugging Face
  • Experience with one or more of the following : Deep learning methodologies (., sequence-based or representation learning models)Transformer architectures (., BERT, GPT, ViT) for NLP and / or visionMultimodal embedding techniques across text, image, audio, or structured dataLarge language models and related evaluation methodologiesRetrieval-augmented generation (RAG) architectures
  • Experience building systems on cloud-native infrastructure and distributed platforms
  • Proven ability to thrive in a fast-paced, data-driven, and collaborative environment
  • Preferred Qualifications :

  • Experience in digital video advertising or the digital marketing domain
  • Experience with programmatic advertising or real-time bidding platforms
  • MS or PhD (preferred) in Computer Science or equivalent practical experience
  • The hiring range for this position in Glendale, California is $141,900 to $190,300 per year, Santa Monica, California is $141,900 to $190,300 per year, and Seattle, WA is $148,700 to $199,400 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and / or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and / or other benefits, dependent on the level and position offered.

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