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Senior Machine Learning Engineer
Build and deploy scalable machine learning models, pipelines, and production systems for Disney’s Commerce technology business. Guide ML architecture, MLOps practices, and technical work across engineering initiatives.
संयुक्त राज्य
कैलिफ़ोर्निया
फ़्लोरिडा
वॉशिंगटन$1,37,200 – $2,02,400 / वर्ष
हाइब्रिडपूर्णकालिकवरिष्ठआवश्यक भाषा: अंग्रेज़ीमशीन लर्निंग इंजीनियरविवरण
- Design and develop machine learning models, pipelines, and production systems.
- Advance ML components through your work and collaboration with other engineers.
- Create technical solutions that meet specifications and shape future ML initiatives.
- Deliver ML projects and major model improvements using new or existing technologies.
- Define specifications for assigned ML components, projects, and model enhancements.
- Review and write code for model training, evaluation, and inference pipelines.
- Help set the architectural direction for ML platforms and data infrastructure.
- Design ML components for projects and document their specifications.
- Build and lead workflows spanning data ingestion through model serving.
- Coordinate deliverables with data science, data engineering, and product teams across the organization.
- Develop system specifications for assigned ML projects.
- Provide senior technical guidance to less experienced ML engineers and data scientists.
- Lead teams in problem analysis, model debugging, and issue resolution.
आवश्यकताएँ
- At least five years of relevant experience designing, training, and deploying machine learning models at scale in production.
- Experience with Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Strong grasp of supervised and 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 ML services and infrastructure such as AWS SageMaker, EC2, and S3.
- Experience with data pipeline and orchestration tools such as Airflow, Spark, and Kafka.
- Familiarity with databases and storage technologies such as DynamoDB, Redshift, and NoSQL.
- Familiarity with Docker, Kubernetes, and containerization.
- Familiarity with data manipulation tools.
- Experience with Snowflake is required.
- 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 integrating generative AI into production systems.
- Java experience, including Spring Boot, is a plus.
- Bachelor’s degree in Computer Science, Statistics, Mathematics, or a similar field, or related work experience.
लाभ
- A bonus and/or long-term incentive units may be included in the compensation package.
- Medical benefits.
- Financial benefits.
- Other benefits.
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