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Machine Learning Engineer/AI Engineer

Salary undisclosed

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Job Description

Job Description

Job Title: Machine Learning Engineer/AI Engineer

Duration- 5 months

Working hours: 8 AM -5 PM

Work address: Cupertino, CA 95014

Summary of the Project:

We will develop an AI/ML Model Inferencing Pipeline that would automate the extraction of all data elements from the Document or from Source Streaming Data, this will leverage the elastic nature of cloud for cost optimize for different use cases.

Responsibilities:

You will design, develop, test, deploy, maintain, and enhance Machine Learning Pipelines using K8s/AKS based Argo Workflow Orchestration solutions

Participate and contribute in design reviews with platform engineering team to decide the design, technologies, project priorities, deadlines, and deliverables

You will work closely with Data Lake and Data Science team to understand their data structure and machine learning algorithms

Understanding of ETL pipelines, and ingress / egress methodologies and design patterns

Implement real time argo workflow pipelines, integrate pipelines with machine learning models, and translate data and model results into business stakeholders Data Lake

Develop distributed Machine Learning Pipeline for training & inferencing using Argo, Spark & AKS

Build highly scalable backend REST APIs to collect data from Data Lake and other use-cases / scenarios

Deploy Application in Azure Kubernetes Service using GitLab CICD, Jenkins, Docker, Kubectl, Helm and Mainfest

Experience in branching, tagging and maintaining the versions across the different environments in GitLab

Review code developed by other developers and provide feedback to ensure best practices (e.g., checking code in, accuracy, testability, and efficiency)

Debug/track/resolve by analyzing the sources of issues and the impact on application, network, or service operations and quality

Functional, benchmark & performance testing and tuning for the built workflows

Assess, design & optimize the resources capacities (e.g .Memory, GPU etc.) for ML based resource intensive workloads

Required Skills

Bachelor s/Master s degree in Computer Science or Data Science

5 to 8 years of experience in software development and with data structures/algorithms

5 to 7 years of experience with programming language Python or JAVA, database languages (e.g., SQL), and no-sql

5 years of experience in developing large-scale infrastructure, distributed systems or networks, experience with compute technologies, storage architecture.

Strong understanding of micro services architecture and experience with building and deploying RestAPI s using Python, Flask and Django

5 years of experience with Unit and Functional test cases using PyTest, UnitTest and Mocking External Services for functional and non-functional requirements

Strong understanding and experience with Kubernetes for availability and scalability of the application in Azure Kubernetes Service

Experience in building and deploying applications with Azure, using third-party tools(e.g., Docker, Kubernetes and Terraform)

Experience with cloud tools like Azure and Google Cloud Platform

Experience with development tools, CI/CD pipelines such as GitLab CI/CD, Artifactory, Cloudbees and Jenkins

Preferred Skills

Python, Kubernets, Argo Workflow, Argo Event, Hive, SQL, no-sql, RestAPI s, Helm, Docker, Jenkin

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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