Azure Machine Learning Engineer

Job Summary:

We are seeking an Azure Machine Learning MLOps Engineer to work in AI/ML team.

As an ML Engineer, you'll be responsible for design, development and implementation of all cycles of MLOps including test, staging, monitoring and deployment of predictive models on cloud-based platform specifically Azure cloud. ML Engineer needs to ensure that our machine learning systems are reliable, scalable, and secure, and that they meet the needs of our customers.

The ideal candidate will have an extended experiences of deployment and maintaining of AI / ML models in production, a deep understanding of the latest developments in machine learning & artificial intelligence and working experience with both structured and unstructured data.

Job Responsibilities:

• Collaborate closely with the AI / ML and software teams to improve the internal processes and integrate the Machine Learning models into our products and services.
• MLOps and Automation that cover automating data pipelines, monitoring data processes, and managing deployments using tools like Azure DevOps, Azure Monitor, and Azure Automation to achieve continuous integration and delivery (CI/CD).
• Deploy and manage AI/ML models in production.
• Automating AI/ML model deployment and updating.
• Setting up monitoring for the AI/ML pipeline.
• Automating scalable CI/CD pipelines to account for data, codes, and model changes.
• Development and setting up automated model retraining and test pipelines.
• Prepare unit tests for AI / ML algorithms and models.
• Contribution in design, development, and test of data ETL pipelines for ML models.
• Provides best practices and running proof-of-concepts for automated and efficient model operations on a large scale.
• Maintaining the infrastructure that supports the models and algorithms.
• Design, build and deploy powerful BI solutions as per business requirements.
• Participate in modeling Relational and NoSQL databases.
• Host and optimize ML Artifacts on premise and on the cloud.
• Contribution in projects documentation.
• Investigating new technologies that meet corporate standards to enhance the team.
• Work in a team oriented and agile environment based on designed scrums, sprints and daily stand ups.
• Ability to work on your own and with the team.
• Performs other duties as assigned.

Qualifications:

You MUST have the following:

• Bachelor's degree in computer science, Computer Engineering, Machine Learning, or related areas.
• Proven experience as a ML Ops Engineer or similar role.
• Understanding of data structures, data modeling and software architecture.
• Ability to design and implement cloud solutions.
• Ability to write robust codes in SQL and Python.
• Experience working with Containers and Kubernetes.
• High level knowledge of frameworks such as Keras, PyTorch, Tensorflow.
• Ability to build MLOps pipelines including CI/CD Configuration Management, Containers & Infrastructure Orchestration.
• Experience with software development and preparation of Python packages.
• Experience in using MLOps frameworks like MLFlow.
• Working knowledge of orchestrating end to end ML pipelines.
• Deep understanding of Azure, Private Networking, ML Studio and its sub-components, Azure Synapse, Azure DataBricks, Azure Stream Analytics, Azure Data factory, OpenAI, Github Actions, and Azure DevOps.
• Experiences with version control tools such as Github.
• Work experiences with typical data storage technologies and methodologies included data warehouse and data lake.
• Work experience with APIs.
• Expertise in SQL, NoSQL databases.
• Ability to write Linux/Unix Shell Scripting.
• Excellent communication skills.
• Ability to work in a team.
• Outstanding analytical and problem-solving skills.

Working Hours:

Eastern Standard Time (EST)