| AI - DevOps lead - Remote at Remote, Remote, USA |
| Email: [email protected] |
| From: Ravi Teja, GAC Solutions [email protected] Reply to: [email protected] Job Title: AI/DevOps lead Location: Remote Duration: Contract Job Description Model Deployment: Infrastructure: Setting up the necessary computational resources, such as GPUs or TPUs, and cloud services to run large language models. Scalability: Ensuring that the infrastructure can handle variable loads and scale up or down based on demand. Model Monitoring: Performance Tracking : Continuously monitoring model performance in terms of speed, accuracy, and resource usage. Error Logging : Keeping logs of errors or anomalies to identify and address issues promptly. Model Maintenance: Updates and Upgrades : Regularly updating the model with new data or upgrading to more advanced versions to improve performance and accuracy. Bug Fixes: Identifying and fixing bugs or issues that arise during model operation. Data Management: Data Collection : Gathering new data for training, fine-tuning, or evaluating the model. Data Cleaning : Ensuring that the data used is clean, relevant, and free of biases. Security and Compliance: Data Privacy : Ensuring that data used for training and inference complies with privacy regulations (e.g., GDPR, CCPA). Model Security : Protecting the model and data from unauthorized access or malicious attacks. Optimization: Performance Tuning : Adjusting model parameters, algorithms, and infrastructure to optimize performance and resource utilization. Cost Management: Managing the costs associated with running large models, including computational resources and cloud services. User Feedback and Iteration: Feedback Loops : Incorporating feedback from users to improve model performance and usability. Iterative Development : Continuously refining and improving the model based on new data, feedback, and technological advancements. Ethical and Responsible AI: Bias Mitigation: Identifying and reducing biases in model outputs to ensure fairness and equity. Transparency: Making model operations and decisions transparent to users and stakeholders. Integration and API Management: APIs and Endpoints: Developing and managing APIs for easy integration of language models into applications and services. Compatibility: Ensuring that the model works seamlessly with different platforms and tools. Documentation and Training: Documentation: Providing clear and comprehensive documentation for developers and users. Training and Support: Offering training and support to users and teams working with the model." Keywords: artificial intelligence AI - DevOps lead - Remote [email protected] |
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| Fri Aug 02 02:23:00 UTC 2024 |