| AI-ML Engineer at Austin, Texas, USA |
| Email: [email protected] |
| From: Vinod Kumar, Excel Hire Staffing, LLC [email protected] Reply to: [email protected] Job Title: AI/ML Engineer Duration: 12 months Location: Austin, TX Hours: 2080 Texas GovLink, Inc. is an Austin-based firm which has been a premier provider of technical and business professionals to clients in Texas. We are currently seeking an experienced AI/ML Engineer to be a key resource on a technical services team. Responsibilities: We are seeking a talented and innovative AI / Machine Learning Engineer to join our team. As part of the AI Technical Team, you will design, build, and deploy advanced machine learning models and AI solutions to solve real-world problems. You will work with large datasets, AI/ML frameworks, and cross-functional teams to deliver impactful results that align with our business goals. If you are passionate about machine learning, artificial intelligence, and creating high-performance models, wed love to hear from you. Key Responsibilities Model Development and Design: Develop, test, and optimize machine learning models for classification, regression, clustering, or recommendation tasks. Data Preparation: work alongside the Enterprise Data Management Team to collect, clean, preprocess, and analyze large datasets to create high-quality training datasets. Algorithm Implementation: Implement machine learning algorithms and neural networks using frameworks like TensorFlow, PyTorch, and scikit-learn. Deployment and Integration: Deploy trained models into production environments using APIs, containers (e.g., Docker), or cloud services (AWS, GCP, or Azure). Performance Monitoring: Monitor model performance, detect drift, and implement improvements or retraining strategies to ensure models remain accurate over time. Collaboration: Work closely with our data management team, applications team, enterprise architects, and product managers to align solutions with business needs. Documentation: Create thorough documentation for models, processes, and experiments to ensure reproducibility and scalability. MLOps Practices: Develop automated pipelines for continuous integration, delivery, and model retraining (CI/CD). Ethics and Compliance: Ensure AI models comply with industry regulations, address biases, and adhere to ethical standards. Keywords: continuous integration continuous deployment artificial intelligence machine learning Texas AI-ML Engineer [email protected] |
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| Tue Nov 05 02:51:00 UTC 2024 |