AunAliakaCossale

• Create and deploy AI agents to production: Design, develop, and implement intelligent AI agents capable of performing specific tasks or functions. Ensure these agents are seamlessly integrated into live operational environments, optimized for performance, scalability, and reliability to support business objectives.

• Oversee model training and evaluation: Lead the end-to-end process of training machine learning models, including data collection, preprocessing, and feature engineering. Rigorously evaluate model performance using appropriate metrics, validate their accuracy, and fine-tune parameters to ensure the deployment of robust and effective AI solutions.

• Lead, build, and support the team of AI/ML professionals: Provide strategic leadership and technical guidance to a team of data scientists, machine learning engineers, and AI specialists. Foster a collaborative and innovative work environment, facilitate skill development, and ensure the team's efforts align with organizational goals.

• Build and deploy AI solutions to production: Architect and develop comprehensive AI-based applications and systems. Manage the deployment process, including testing, validation, and integration with existing infrastructure, to deliver scalable, secure, and maintainable AI solutions that drive business value.

• Website

• Python
• PyTorch
• HF Transformers/Diffusers/Datasets
• Axolotl
• Unsloth
• TRL

• Fine-tune Large Language Models (LLMs): Specialized in fine-tuning LLMs for specialized tasks including role-play scenarios and question-answering systems. This work improves model performance for specific use cases.

• Fine-tune Diffusion Models: Work on fine-tuning diffusion models, particularly Stable Diffusion, for custom image generation tasks. This involves creating and curating datasets tailored to project requirements.

• Implement Reinforcement Learning (RL) techniques: Applied techniques such as Direct Preference Optimization (DPO), KTO, ORPO to better align models with user preferences, resulting in improved output quality and user satisfaction.

• Develop and deploy a moderation API: Utilized vision models to detect harmful content, addressing important safety concerns in AI applications.

• Create automation scripts: Developed and maintained automation scripts for LLM hosting, benchmarking, and synthetic data generation. These efforts streamline development processes and improve team efficiency.

• Ongoing learning: Engaged in ongoing learning and application of emerging AI techniques, staying current with advancements in the field.

• Website

• Python
• PyTorch
• HF Transformers/Diffusers/Datasets
• Axolotl
• Unsloth
• TRL

• Worked with a globally distributed team of 15 developers to build ReVanced, an open-source Android modification framework empowering users to customize apps to suit their needs.

• I helped spearhead overall architecture, design, and roadmapping - devising an adaptable core to enable endless customizations for apps built on Dalvik like YouTube. I also directly contributed extensive code across the codebase.

• I led development of the ReVanced Manager app installed by over 170K users. The app streamlined installations and made core functionality easily accessible.

• Initially adopted by a few hundred users, ReVanced gathered incredible traction on platforms like Reddit, Discord and Telegram from folks who really liked what we built.

• As installs grew exponentially to 170,000+, I took on expanded duties - overseeing roadmap priorities, debugging complex issues, liaising with user communities, and ensuring stability through rigorous testing.

• The project gave me hands-on experience on how coordinated remote teams can build delightful products loved by users globally. Debugging performance problems taught me how to approach issues methodically. Ultimately, the ability to solve real user problems at scale was extremely fulfilling.

• Website GitHub

• Flutter
• Dart
• Kotlin
• JADX