Job Description:
Job Description
Utilizes complex knowledge of machine learning engineering concepts and principles to apply skills in a business environment. Primarily focused on productionizing machine learning models and systems at scale.
Essential Job Functions (3-5 years of related experience required):
- Delivers specific ML Ops engineering tasks such as moderate to complex level designing, developing, implementing, optimizing, and maintaining models, systems, and applications using existing and emerging technology platforms.
- Collaborates with cross-functional architecture teams to define and integrate frameworks and roadmaps for machine learning solutions.
- Projects are generally of moderate complexity.
- Consults on the design, development, and implementation of DevOps and ML Ops pipelines.
- May lead portions of deployment processes under guidance from people leader.
- Reviews, verifies, validates, and troubleshoots code to ensure high availability and high performance of machine learning models and applications.
- Uses complex knowledge and understanding of code management principles and best practices to follow architectural and governance guidelines.
- Effectively communicates and applies machine learning engineering value, concepts, and strategies across multiple scenarios.
Additional Qualification:
- Demonstrated analytical skills. Demonstrated problem solving skills. Possesses strong technical aptitude.
- Experience with building and maintaining end-to-end machine learning pipelines in production environments.
- Experience with model and data versioning, model deployment, model serving and monitoring. Intermediate knowledge of workflow orchestration processes and technologies.
- Ability to simultaneously handle multiple priorities.
- Seeks to acquire knowledge in area of specialty.
Special Skill Requirements (3-5 years of related experience required):
- Strong Coding experience with Python
- Object Oriented Programing
- AWS - SageMaker
- Git, GitHub
Additional Qualification:
- Demonstrated analytical skills.
- Demonstrated problem solving skills.
- Possesses strong technical aptitude.
- Experience with designing and building scalable enterprise ML Ops frameworks and pipelines including integration, testing, deployment, monitoring, infrastructure management, audit and governance.
- Advanced understanding and practical application of workflow orchestration processes and technologies.
Once you apply for this position, you may receive a phone call, SMS or email from our Virtual Recruiter, Alex, to conduct an initial interview.
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