Job#: 1274503 Job Description:
One of Apex Systems top Industrial clients is looking for a full time Senior ML Engineer! (CAN BE FULLY REMOTE)
As a Senior Machine Learning Engineer,
you'll contribute to specific business projects applying machine learning, DevOps, code optimization, and data visualization methods to drive deployment of AI products. You will make recommendations on the machine learning pipelines architecture, as well as infrastructure and performance recommendation for resource creating and successful operationalization of such AI products!
You will establish and integrate ML Operations into everyday work practice for AI teams using industry best practices and patterns. You will play a part in the development of features and operating model, that will result in the lowest total cost of ownership and assure the fastest delivery. Key Responsibilities:
- Hands-on design and development of integrated build and deployment pipelines using continuous integration (CI) and continuous delivery (CD) workflows (Azure DevOps). Governance of the build and release pipelines.
- Configuration and provisioning of compute infrastructure; automation scripting (Azure Data Lake and Spark, infrastructure as code).
- Full lifecycle development of endpoint services (APIs) and infrastructure at scale (Microsoft managed endpoints, APIs).
- Working with data science experimental code base (notebooks) to apply the best software engineering practice and refactor for deployment (Python, YAML, C#)
- Actively participate in platform administration (Microsoft Azure) and collaborating closely with the platform administration team to ensure compliance.
- Translating data science requirements into code and performing in agile fashion.
- Working within Agile SCRUM framework and leading technical design; assisting junior developers in task definition and execution by providing mentorship.
- Bachelors in Computer Science and Programming; Masters in Systems Engineering, Masters in Information Technology considered a strong asset.
- 3+ years of demonstrated proficiency in machine learning, with experience in deployments and ML architecture design
- Proficiency with Python, SQL, C#
- Experience using Microsoft DevOps portal
- Azure/AWS Cloud certification, DevOps certification, and Agile Methodology certification an asset.
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