AI Architectural Engineer
12 hours ago
We are seeking a highly skilled AI Architectural Engineer to join our team at Unreal Gigs. As an AI Architectural Engineer, you will play a critical role in designing and developing cutting-edge AI solutions that transform industries.
About the Role:
- Design and Develop AI Models: You will be responsible for designing, building, and deploying machine learning and AI models using frameworks like TensorFlow, PyTorch, or Scikit-learn. Your expertise will focus on projects involving natural language processing (NLP), computer vision, predictive analytics, and more.
- Data Engineering and Feature Engineering: Collaborate with data engineers and scientists to collect, preprocess, and transform large datasets for model training. You will ensure that data pipelines are optimized for AI workflows and support the development of high-performance models.
- Optimize Model Performance: Experiment with different model architectures, algorithms, and hyperparameters to improve accuracy, speed, and scalability.
- Deploy Models into Production: Work with DevOps and software engineering teams to deploy AI models into production environments, ensuring they are scalable, efficient, and integrated with other systems.
- Monitor and Retrain AI Models: Continuously monitor the performance of deployed models, detecting model drift and updating models as necessary. You will retrain models with new data to keep them accurate and relevant in changing environments.
- Cross-Functional Collaboration: Work closely with product managers, engineers, and other stakeholders to understand business needs and translate them into AI solutions. You will ensure that AI models align with product goals and deliver measurable business outcomes.
Requirements:
- AI and Machine Learning Expertise: Deep understanding of machine learning algorithms, such as decision trees, neural networks, clustering, and reinforcement learning. Experience in developing models for NLP, computer vision, and predictive analytics.
- Programming and AI Tools: Proficiency in programming languages like Python or R, and experience using machine learning frameworks such as TensorFlow, PyTorch, Keras, and Scikit-learn.
- Data Engineering and Feature Engineering: Hands-on experience with data preprocessing, feature selection, and engineering for AI models.
- Deployment and Integration: Experience deploying AI models into production environments using cloud platforms (AWS, GCP, Azure) and containerization tools like Docker and Kubernetes.
Compensation: The estimated salary for this position is $120,000 - $180,000 per year, depending on experience.
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