Artificial Intelligence Deployment Specialist

3 weeks ago

Noida, Uttar Pradesh, India SDLC Corp Full time
MLOps Engineer
About the Role

At SDLC Corp, we are seeking an experienced MLOps Engineer to join our team. The ideal candidate will have a strong background in machine learning and cloud computing.


Key Responsibilities

  • Deploy and manage machine learning models in production environments, ensuring high availability and performance.
  • Automate the deployment process using CI/CD pipelines, ensuring that models are deployed efficiently and reliably.
  • Develop and maintain scripts and tools for automating model training, deployment, and monitoring.
  • Monitor the performance of deployed models, identifying and resolving issues proactively.
  • Implement monitoring tools and dashboards to track model performance metrics, detect anomalies, and ensure scalability.
  • Perform regular maintenance tasks, including model retraining, updates, and scaling to handle increased data loads.
  • Work closely with data scientists to understand model requirements and ensure smooth integration into production systems.
  • Collaborate with software engineers to integrate machine learning models into existing applications and services.
  • Partner with data engineers to build and maintain data pipelines that feed into machine learning models.
  • Manage and optimize the infrastructure required for machine learning operations, including cloud platforms, Kubernetes clusters, and containerized environments.
  • Ensure that the infrastructure is scalable, secure, and cost-effective.
  • Implement best practices for infrastructure as code (IaC) and manage configuration using tools like Terraform or Ansible.
  • Apply DevOps principles to machine learning operations, including continuous integration, continuous delivery, and automated testing.
  • Use version control systems (i.e., Git) to manage code and model versioning.
  • Implement and manage containerization using Docker and orchestration using Kubernetes.
  • Troubleshoot and resolve issues related to model deployment, infrastructure, and performance.
  • Optimize model deployment processes to reduce latency and improve scalability.
  • Continuously evaluate and implement new tools and technologies to improve ML Ops practices.

Requirements

Education:



  • Bachelor's degree in Computer Science, Information Technology, or a related field.

Technical Skills:



  • Proficiency in machine learning techniques and model deployment, with experience in automating these processes.
  • Strong programming skills in Python, Java, or other relevant languages.
  • Experience with DevOps tools such as Jenkins, Git, Terraform, or Ansible.
  • Expertise in containerization (Docker) and orchestration (Kubernetes).
  • Experience with cloud platforms (i.e., AWS, GCP, Azure) for deploying and managing machine learning models.
  • Knowledge of data engineering concepts, including data pipelines and ETL processes.

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