Cloud Analytics - Application PhD Intern

• →Design, develop, and maintain scalable machine learning pipelines for data processing, model training, and inference in cloud and on-premises environments.
• →Develop and deploy APIs and microservices that interact with various components of ML-powered applications.
• →Utilize containerization technologies such as Docker and orchestration systems like Kubernetes to package, scale, and manage ML services.
• →Accelerate deployment cycles using Intel manufacturing's cloud-native ML platforms based on Kubernetes/Rancher.
• →Implement MLOps best practices, including model versioning, monitoring, and continuous integration/continuous deployment (CI/CD).
• →Collaborate cross-functionally with software developers, data scientists, and DevOps engineers to integrate ML capabilities into Intel's manufacturing processes seamlessly.
• →Optimize the performance, latency, and cost efficiency of deployed ML models.

• Currently enrolled in Ph.D. program in Computer Science, Software Engineering, or a related technical field.
• Strong programming skills in Python, and solid understanding of software engineering principles, including data structures, algorithms, and object-oriented design.
• Prior experience working with python client libraries to interact with SQL based databases, optimize queries and perform inserts/updates per application needs.
• Hands-on experience with Docker and cloud deployment technologies.
• Knowledge of machine learning concepts and the model development lifecycle.
• Familiarity with CI/CD tools and practices such as Jenkins, GitLab CI, or GitHub Actions.

• Prior experience with OpenCV, Pytorch, YOLO and/or VLM models for Computer vision AI/ML projects
• Experience with MLOps tools like MLflow or Kubeflow.
• Familiarity with Kubernetes and Rancher for orchestration.
• Strong problem-solving skills and a passion for building robust, scalable systems.
• Demonstrated ability to work collaboratively in a cross-functional team environment.
• 3.0 GPA or higher is preferred along with previous internship experience in an enterprise environment.
  
  

Take the next step in your career and join Intel's innovative team, where your contributions will help shape the future of technology. Apply today to make an impact.

*