Audio Machine Learning Co - op developing real - time AI - powered audio processing algorithms for Bose. Collaborating with experts to prototype and implement novel ML algorithms for various applications.
About the role
- Lead Machine Learning Engineer developing and deploying ML systems for Disney's advertising solutions. Collaborating with cross-functional teams to drive innovation in media technology.
Responsibilities
- Lead the design and delivery of machine learning solutions across advertising use cases such as inventory forecasting, pricing, targeting, and efficient ad delivery
- Apply modern machine learning techniques to solve complex, real-time advertising problems
- Provide technical leadership for ML system architecture, modeling approaches, and production readiness within your domain
- Design, build, and scale ML architectures that balance model quality, latency, throughput, reliability, and cost
- Oversee the full ML lifecycle for owned systems, from experimentation through production deployment and iteration
- Design and maintain feature pipelines and feature stores supporting both real-time inference and offline training
- Partner with product and engineering stakeholders to translate requirements into clear technical plans and measurable outcomes
- Interpret experimental results and guide data-informed decision-making
- Ensure ML systems are observable, debuggable, and explainable in production
- Establish and maintain monitoring for model performance, drift, bias, and system health
- Champion engineering excellence through best practices in code quality, system design, testing, and operational reliability
- Mentor and support engineers through code reviews, design discussions, and ongoing technical guidance
Requirements
- Bachelor's in Computer Science or equivalent practical experience
- 7+ years of software engineering experience
- 5+ 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 ML frameworks and tooling such as TensorFlow, PyTorch, and Hugging Face
- Experience with deep learning methodologies (e.g., sequence-based or representation learning models)
- Experience building systems on cloud-native infrastructure and distributed platforms
Benefits
- A bonus and/or long-term incentive units may be provided as part of the compensation package
- Full range of medical, financial, and/or other benefits, dependent on the level and position offered
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