Senior ML Engineer: Scalable Models & MLOps

Oxford Global Resources; Gaithersburg (MD); Presencial; USD 37 000 - 50 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Medical benefits

401(k) plan

Paid holidays

Paid sick leave

Disability accommodation

Resumo da oferta

Oxford Global Resources seeks an experienced ML Engineer to design, develop, and deploy scalable ML models and data pipelines in real-world applications. You will collaborate with data scientists and software engineers to optimize performance and ensure security and compliance across the development lifecycle.

Responsibilities include building robust pipelines, implementing monitoring and drift detection, and maintaining documentation for model architecture and deployment workflows.

Qualificações

• 5+ years of experience in machine learning engineering or related roles.
• Solid foundation in computer science and applied mathematics.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud ML services (SageMaker, Vertex AI, Azure ML).
• Experience with Docker and Kubernetes.
• Strong understanding of data structures, algorithms, and software engineering principles.
• Familiarity with MLOps: CI/CD for ML, model versioning, automated deployment.
• Experience with large-scale datasets and distributed computing.
• Knowledge of ethical AI, model interpretability, and fairness in ML.

Responsabilidades

• Design, develop, and deploy scalable ML models and systems.
• Build and maintain data pipelines to support training and inference.
• Implement monitoring, logging, and drift-detection in production.
• Collaborate with data scientists, software engineers, and product teams.
• Ensure models meet security, privacy, and compliance standards.

Conhecimentos

Python

TensorFlow

PyTorch

Scikit-learn

Cloud services

Docker

Kubernetes

MLOps

CI/CD

Distributed computing

Ferramentas

Docker

Kubernetes

Descrição da oferta de emprego

Oxford Global Resources seeks an experienced ML Engineer to design, develop, and deploy scalable ML models and data pipelines in real-world applications. You will collaborate with data scientists and software engineers to optimize performance and ensure security and compliance across the development lifecycle.

Responsibilities include building robust pipelines, implementing monitoring and drift detection, and maintaining documentation for model architecture and deployment workflows.