Sr Machine Learning Engineer

Disney Cruise Line - The Walt Disney Company; Orlando (FL); On-site; Confidential; Full time

Job summary

Disney Cruise Line – The Walt Disney Company seeks a Senior Machine Learning Engineer to design, train, and deploy scalable ML models, pipelines, and systems. You will own ML solutions and guide other engineers while driving delivery and architectural decisions.

The role requires strong Python and ML framework experience, MLOps expertise, and knowledge of cloud services and data infrastructure. Florida location with competitive compensation.

Qualifications

• 5+ years of experience designing, training, and deploying ML models in production at scale.
• Experience with Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Strong understanding of ML fundamentals including supervised/unsupervised learning, model evaluation, and feature engineering.
• Expertise in MLOps practices including model versioning, experiment tracking, CI/CD for ML, and model monitoring.
• Experience with cloud-based ML services and infrastructure (e.g., AWS SageMaker, EC2, S3).
• Experience with data pipeline and orchestration tools (e.g., Airflow, Spark, Kafka).
• Familiarity with database and data storage technologies (e.g., DynamoDB, Redshift, NoSQL), containerization (Docker, Kubernetes), and data manipulation tools.
• Experience with Snowflake is required.

Responsibilities

• Owns the design and development of machine learning models, pipelines, and production ML systems.
• Drives development of ML components through own and other engineers' work.
• Develops technical solutions that meet specifications and inform future ML initiatives.
• Executes assigned ML projects and major model improvements using new or existing technologies.
• Develops specifications for ML components, projects, or model enhancements; reviews and writes code for training, evaluation, and inference pipelines.
• Participates in setting the architectural direction for ML platforms and data infrastructure.
• Designs ML components for assigned projects, developing specifications for each.
• Builds and leads end-to-end ML workflows from data ingestion through model serving.
• Interacts with data science, data engineering, and product teams across the organization.
• Designs and develops ML system specifications for assigned projects.
• Designs component tasks for assigned projects, developing ML-specific specifications.
• Serves as a high-level technical resource and go-to person for less experienced ML engineers and data scientists.
• Leads team members in problem analysis, model debugging, and issue resolution.

Skills

Python

TensorFlow

PyTorch

scikit-learn

MLOps

AWS SageMaker

Airflow

Spark

Kafka

Docker

Kubernetes

Snowflake

DynamoDB

Redshift

NoSQL

Java

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

Airflow

Spark

Kafka

Snowflake

DynamoDB

Redshift

NoSQL

AWS SageMaker

EC2

S3

Job description

The Senior Machine Learning Engineer applies practical knowledge of machine learning, data science, and software engineering to conceive, design, develop, train, and deploy ML models, pipelines, and systems of moderate to high complexity. The Senior Machine Learning Engineer owns the design and development of ML solutions and drives their delivery through their own and other engineers' work. The Senior Engineer provides technical guidance and acts as a point of escalation and as a machine learning expert. The Senior Machine Learning Engineer designs and develops highly scalable ML systems and data pipelines.

Responsibilities

• Owns the design and development of machine learning models, pipelines, and production ML systems.
• Drives development of ML components through own and other engineers' work.
• Develops technical solutions that meet specifications and that inform future ML initiatives.
• Executes assigned ML development projects and major model improvements using new or existing technologies.
• Develops specifications for assigned ML components, projects, or model enhancements.Reviews and writes code for model training, evaluation, and inference pipelines.
• Participates in setting the architectural direction for ML platforms and data infrastructure.
• Designs specific ML components for assigned projects, developing specifications for each.
• Able to build and lead end-to-end ML workflows from data ingestion through model serving.
• Interacts and coordinates deliverables with data science, data engineering, and product teams across the organization.
• Designs and develops ML system specifications for assigned projects.
• Designs component tasks for assigned projects, developing ML-specific specifications for each.
• Serves as a high-level technical resource and "go-to" person for less experienced ML engineers and data scientists, providing technical guidance and oversight.
• Leads team members in problem analysis, model debugging, and issue resolution.

Basic Qualifications

• 5+ years of relevant experience designing, training, and deploying machine learning models in production environments at scale.
• Experience with Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Strong understanding of ML fundamentals including supervised/unsupervised learning, model evaluation, and feature engineering.
• Strong expertise in MLOps practices including model versioning, experiment tracking, CI/CD for ML, and model monitoring.
• Experience with cloud-based ML services and infrastructure (e.g., AWS SageMaker, EC2, S3).
• Experience with data pipeline and orchestration tools (e.g., Airflow, Spark, Kafka).
• Familiarity with database and data storage technologies (e.g., DynamoDB, Redshift, NoSQL), containerization (Docker, Kubernetes), and data manipulation tools.
• Experience with Snowflake is required.

Preferred Qualifications

• Experience with large-scale recommendation systems, personalization, NLP, or computer vision.
• Experience with real-time ML inference and low-latency serving architectures.
• Familiarity with LLMs and generative AI integration in production systems.
• Experience with Java (e.g., Spring Boot) is a plus.

Required Education

• Bachelor's degree in Computer Science, Statistics, Mathematics, or similar field, or related work experience.

The hiring range for this position in Florida is $135,200.00-$181,200.00 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.