Machine Learning Engineer
4 weeks ago
Job Title: Machine Learning Engineer
Job Summary:
The Machine Learning Engineer position at UPS plays a crucial role in the development and maintenance of Machine Learning (ML) models and software components that solve complex business problems. This position collaborates with cross-functional teams to assess and analyze large-scale data sources, identifying opportunities for ML and Artificial Intelligence (AI) automation.
Responsibilities:
- Design and implement ML models in production environments, ensuring seamless integration with existing systems.
- Monitor model performance using established metrics and identify potential issues like performance degradation, drift, or bias.
- Participate in the response and resolution of production incidents, minimizing downtime and impact on business operations.
- Collaborate with stakeholders to diagnose and fix problems.
- Maintain documentation for deployed models, including deployment logs, monitoring dashboards, and troubleshooting procedures.
- Ensure model compatibility with new software versions and infrastructure changes.
- Archive and manage different model versions for auditability and rollback capabilities.
- Analyze logs, error messages, and other data to diagnose model issues.
- Utilize debugging tools and techniques specific to machine learning.
- Reproduce and isolate issues in test environments before fixing them in production.
- Document bug fixes and lessons learned to improve future model development and maintenance.
- Analyze monitoring data proactively to identify trends and potential issues before they impact production.
- Stay up-to-date on new monitoring tools and techniques for machine learning systems.
- Report on model performance and health to stakeholders regularly.
- Stay up-to-date on advances in machine learning and best practices for production usage.
- Contribute to documentation and knowledge sharing within the team.
Qualifications:
- Demonstrated proficiency in Python, SQL, and cloud platforms such as GCP, AWS, or Azure.
- Experience in DevOps practices for supporting and maintaining applications and products driven by Machine Learning (ML) and Artificial Intelligence (AI).
- Expertise in developing and optimizing ML pipelines.
- Understanding and experience in scaling solutions for ML and AI applications.
- Demonstrate experience in various ML frameworks such as Python, Scala, or Java for debugging and developing minor enhancements to models.
- Proficiency in deploying and managing models using Kubernetes.
- Experience in supporting products with capabilities including Deep Learning, Supervised, and Unsupervised techniques.
- Familiarity with implementing solutions using Python, Scala, or Java.
- Ability to utilize visualization tools for model monitoring and management in production.
- Experience in deploying and managing machine learning models using containerization tools such as Kubernetes, Docker, Fargate, etc.
- Documentation and communication skills for technical and non-technical stakeholders.
- Strong investigative and troubleshooting skills with regards to ML Pipelines.
- Excellent written and verbal communication skills.
- Bachelor's degree in Computer Science or related discipline, or the equivalent in education and work experience.
Preferred Qualifications:
- Comfortable working with data scientists, data engineers, product owners, and architects.
- Background in Agile/Kanban development methodologies.
- Experience working within Agile Frameworks for ML and AI projects.
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