Job Details:

Job Description: 

As a leading technology company, Intel is at the forefront of harnessing the power of artificial intelligence (AI) to revolutionize the way we work and live. Within the People Analytics team in HR, we are seeking a highly skilled MLOps Engineer to help us leverage AI to drive business outcomes.

Our organization is dedicated to using data and analytics to improve the employee experience, enhance HR processes, and drive business success. We are passionate about using data science and AI to automate and optimize HR operations, and we are looking for a talented MLOps Engineer to join our team and help us achieve our goals.

Summary:

The MLOps Engineer within the People Analytics team is a 2-year, contract position in which you will play a critical role in deploying and maintaining machine learning models to improve HR processes and drive business outcomes. You will work closely with data scientists, data engineers, and other stakeholders to architect and optimize the team's cloud-based infrastructure using Azure.

Your primary responsibilities will include but not limited to:  

Build and Maintain CI/CD Pipelines:

• Design, implement, and manage robust Continuous Integration and Continuous Deployment (CI/CD) pipelines for machine learning models and applications.
• Collaborate with cross-functional teams to establish and enhance CI/CD best practices.

Azure Expertise:

• Utilize your expertise in Azure to architect and deploy machine learning solutions within the Azure ecosystem.
• Manage and optimize Azure-based infrastructure, ensuring security, scalability, reliability, and performance.

Machine Learning Model Deployment:

• Implement and manage deployment strategies for machine learning models in development and production environments.
• Collaborate with data scientists and engineers to streamline the deployment process and monitor model performance.

Monitoring and Optimization:

• Create comprehensive testing protocols for machine learning models, ensuring thorough evaluation and validation in different environments.
• Implement automated testing procedures to guarantee the reliability and accuracy of deployed models.
• Develop and implement monitoring solutions to ensure the health and performance of deployed machine learning models.
• Proactively identify and address issues related to scalability, efficiency, and reliability.

Collaboration and Documentation:

• Work closely with data scientists, software engineers, and other stakeholders to understand requirements and integrate machine learning models into the overall system.
• Create and maintain comprehensive documentation for CI/CD pipelines, deployment processes, and infrastructure configurations.

Behavioral traits that we are looking for:

• Excellent communication skills and the ability to train and mentor team members.

Qualifications:

You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field
• 4+ years of experience in AI, machine learning, MLOPS or a related field
• 2+ years experience with Azure and cloud-based infrastructure management  

Preferred Qualifications:

• Master's degree in Computer Science, Engineering, or a related field
• Experience with containerization technologies, such as Docker and Kubernetes. 
• Proficient in Python, R, or other programming languages used in AI and machine learning 
• Experience with machine learning frameworks and libraries, such as TensorFlow, PyTorch, or Scikit-Learn
• Familiarity with data engineering and data processing technologies, such as Apache Spark or Apache Kafka
• Strong expertise in building and maintaining CI/CD pipelines for machine learning applications
• 5+ years of experience in AI, machine learning, or a related field
• Experience with Azure Machine Learning, Azure Data Factory, or other Azure-based AI and machine learning tools
• Strong experience with data visualization tools, such as Tableau or Power BI
• Familiarity with DevOps practices and tools, such as Jenkins or Git
• Experience with Agile methodologies and Scrum frameworks
• Strong understanding of ML algorithms and their applications in HR, such as predictive modeling, sentiment analysis, and text classification.
• Experience with Pipeline Management and/or Dockerization

Anticipated duration: