Sr Machine Learning Engineer

The Walt Disney Company (France)

Orlando (FL)

On-site

USD 135,000 - 181,000

Full time

5 days ago
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Job summary

The Walt Disney Company in Florida seeks a Senior Machine Learning Engineer to design, train, and deploy scalable ML models and pipelines. You will own ML solutions end-to-end, guiding delivery with a team of engineers and data scientists.

You will contribute to ML platforms, data infrastructure, and production systems, applying your expertise in Python, ML fundamentals, and MLOps to drive impactful initiatives at scale.

Qualifications

  • 5+ years designing, training, and deploying ML models in production at scale.
  • Proficient in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
  • Strong ML fundamentals: supervised/unsupervised learning, evaluation, feature engineering.
  • Experience with MLOps: versioning, experiment tracking, CI/CD for ML, monitoring.
  • Experience with cloud-based ML services (AWS SageMaker).
  • Experience with data pipelines and orchestration tools (Airflow, Spark, Kafka).
  • Familiarity with databases (DynamoDB, Redshift, NoSQL), containers (Docker, Kubernetes).
  • Experience with Snowflake is required.

Responsibilities

  • Own the design and development of ML models, pipelines, and production ML systems.
  • Drive development of ML components via own and other engineers' work.
  • Develop technical solutions that meet specs and inform future ML initiatives.
  • Execute ML development projects and major model improvements.
  • Review and write code for model training, evaluation, and inference pipelines.
  • Participate in setting the architectural direction for ML platforms and data infra.
  • Design ML components and specifications for projects.
  • Build and lead end-to-end ML workflows from data ingestion to serving.
  • Coordinate deliverables with data science, data engineering, and product teams.
  • Serve as a high-level technical resource and provide guidance to junior ML engineers.
  • Lead team members in problem analysis, debugging, and issue resolution.

Skills

Python
ML frameworks
MLOps
Data pipelines
Cloud services
Docker/Kubernetes
Snowflake

Education

Bachelor's degree in CS/Statistics/Math

Tools

Snowflake
Airflow
Spark
Kafka
Docker
Kubernetes
AWS SageMaker

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.

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