5+ Years
Machine Learning Engineer
Industry: Media and Entertainment, Logistics
Specialization: Anomaly Detection, Computer Vision
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AI animation platform, driven by machine vision capabilities, to efficiently produce personalized, professional-grade avatars with precision and ease.
Tasks performed: Developed tools for Generative images by using Generative Adversarial Networks to generate images from text input.
Impact Achieved:
Though every organization and implementation will have its own unique profile, modeling can be considering in all sizes of organizations. Regarding companies with higher workload may experience greater benefits as the AI animation platform costs are leveraged to generate savings reduction and redistribution of workforce of Graphic and Animation Designer. As an example modeling in a small size company with 20 employees, and considering that at the first year each designer use the tool just as 30% of they average work. Based on the later within the first year is able to achieve cost reduction of $2,880 labour hours , depending on the size of the company and demand a company will be able to achieve greater benefits since its hour reduction and cost is reduced by a conservative factor of 75% labor hours achieved by the computer (AI tool). And productive designers can be relocated to other labors.
Technologies used: Open CV, numpy , TensorFlow, pytorch , python
Team Composition:
-Full-stack developer
-Backend developer
-UI developer
-Computer vision engineer
-Marketing Manger 1
AI tailored solutions for supply chains designed to optimize enterprise processes, providing clear and intuitive visual outputs for enhanced decision-making.
Tasks performed: Developed algorithms for training statical data to be used in supply chains to increase productivity both in supply and sales planning.
Impact Achieved:
As organizations move forward towards implementation of AI solutions , they will have its own unique profile, companies with higher revenue may experience greater benefits as Supply Chain platform costs are leveraged to generate savings on any size of base business. Consider a small size company of 30 employees with a yearly revenue of $10,000,000 . This company was able to achieve cost savings of $634,085.82 after 2 years of usage of the platform. The latter happens after this organization achieved insight into financial and operational performance they were able to determine where to make changes. They were able to reduce labor costs through improving the efficiency of workforce planning processes by trusting this platform to manage at the first year a 40% rate and by increasing confidence of 10% each year, It allowed them to better aligning staffing need with strategy and budgets. As a result, this organization significantly lowered financial planning labor costs and reduced the frequency of overworked teams. Before planning for sales required 50 hours roughly a Year but after consolidating data within in one point , it improved decision-makers actionability to quickly develop understanding of how changes could impact current and future performance they also had additional financial savings. Total of labor hours saved within 2 years by this platform were 575 hours. Adding a single point of consolidation their supply chain reduced the size while decreasing planning cycle time and data error .
Technologies used: numpy, python, Pandas, scikit-learn
Team Composition:
-Marketing Manger
-Full-stack developer
-Backend developer
-UI developer
-Machine Learning engineer