Senior Machine Learning Engineer for Disney designing production ML systems impacting revenue and viewer experience. Collaborate across teams in low-latency, high-throughput environments.
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
Requirements
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, Transformer architectures, Multimodal embedding techniques, Large language models, Retrieval-augmented generation architectures
Experience building systems on cloud-native infrastructure and distributed platforms.
Proven ability to thrive in a fast-paced, data-driven, and collaborative environment.
Benefits
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.
Senior Machine Learning Engineer at Itaú, driving innovation with data and AI solutions. Collaborating across teams to implement robust machine learning architectures and ensure scalable deployments.
Machine Learning Engineer responsible for developing and deploying advanced ML and AI solutions at Zendesk. Collaborating with stakeholders to deliver impactful business outcomes using latest machine learning technologies.
Lead advanced machine learning model development and optimization at PayPal. Collaborate with teams to deploy scalable ML solutions in production environments.
Senior Machine Learning Engineer at Pivotal Health developing ML systems for healthcare reimbursement. Collaborating across teams to build and maintain reliable, production - grade machine learning systems.
Machine Learning Engineer working with Algorithm team on customer onboarding processes. Focus on execution and automation of models using computer vision and AI in sports industry.
Senior Machine Learning Engineer at Troveo designing and optimizing machine learning pipelines for AI video models. Collaborating with cross - functional teams to build scalable video data solutions.
Software Engineer focusing on ML infrastructure for drug discovery at Genesis AI. Leading engineering efforts to enhance scalable platforms for generative modeling and large - scale simulations.
AI/ML Engineer developing machine learning systems for TymeX's digital banking platform. Collaborating across teams to enhance customer interaction and personalization through AI technology.