Lead advanced machine learning model development and optimization at PayPal. Collaborate with teams to deploy scalable ML solutions in production environments.
About the role
- Lead MLOps initiatives at Salla e-commerce platform, building scalable ML training, deployment, and monitoring pipelines. Collaborate with data scientists and engineers to optimize model performance.
Responsibilities
- Design, build, and maintain scalable MLOps pipelines that foster collaboration between data scientists and engineering teams.
- Implement and manage workflows for model training, validation, deployment, and monitoring.
- Utilize cloud-based platforms (AWS, GCP, or Azure) to provision and manage machine learning resources.
- Develop tools and frameworks that assist in continuous integration and deployment of machine learning models.
- Collaborate with data scientists to understand model requirements and assist in feature engineering and selection.
- Monitor model performance in production, identify issues, and provide recommendations for model optimization.
- Establish best practices for versioning, testing, and documenting machine learning models.
- Stay updated with the latest developments in MLOps tools and methodologies.
- Strong communication skills to relay technical concepts to non-technical stakeholders.
- Excellent problem-solving skills and a proactive approach to addressing challenges.
Requirements
- A minimum of 5 years of experience in software engineering or DevOps with a focus on machine learning operations.
- Strong proficiency in programming languages such as Python and familiarity with machine learning frameworks (TensorFlow, PyTorch, etc.).
- Experience with cloud-based platforms like AWS, GCP, or Azure and their machine learning services.
- Hands-on experience with CI/CD processes specific to machine learning applications.
- Professional Experience tools such as Docker and Kubernetes.
- Strong understanding of database technologies (SQL and NoSQL) and data pipeline tools.
- Experience with monitoring tools and practices for ML models in production.
- Ability to work collaboratively in a cross-functional team environment.
Benefits
- Comprehensive Training & Development programs.
- Performance-based Bonus incentives.
- Flexible Work From Home options.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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