AI ML Engineer at global networking leader, shaping ML strategy and building high - performance systems. Innovating with AI technology to enhance network management and develop flagship products.
TC
Hybrid Lead AI/Machine Learning Engineer – Decision Science
Posted 6 months ago
About the role
- Lead AI/Machine Learning Engineer developing decision science models for Disney's various entertainment segments. Overseeing development and operational excellence of decision science models leveraging AI and ML techniques.
Responsibilities
- Lead the design, construction and maintenance of optimized, efficient and reliable decision science pipelines, processes, and tools
- Provide technical leadership through architectural direction, design reviews, and thoughtful decision-making
- Mentor colleagues on building configurable, modular, and scalable solutions
- Present designs and benefits of created tools to the decision science team, leaders, and partners
- Drive and maintain a culture of quality, innovation, and experimentation
- Collaborate closely with product managers, data scientists, client teams, vendors, and other partners
- Proactively troubleshoot and resolve complex CI/CD or integration issues
- Establish and enforce engineering best practices and operational standards
Requirements
- 7+ years of demonstrated ability to drive complex technical projects from ideation through delivery
- Ability to provide peer leadership to junior colleagues
- Must exhibit proficiency in Python, particularly in areas such as object-oriented programming, exception handling, unit testing, model pipelines
- Experience and familiarity with AI/ML (e.g., LLMs, Knowledge Graphs, GenAI)
- Experience with traditional ML algorithms and statistical modeling techniques
- Proficiency in prompt engineering techniques and approaches
- Knowledge of multiple database and distributed computing architectures/technologies
- Proficiency with modern development tooling, including Git, CI/CD pipelines, containerization, and cloud platforms such as AWS
- Strong understanding of software development methodologies and tools including Agile, Git, CICD, MLOps/DevOps, Docker, SSH, Linux
- Excellent analytical and problem-solving skills
- Strong communication and collaboration skills
- Experience developing applications using Streamlit or RShiny frameworks
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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