

I was once a biochemist trying to make cells behave, now I'm in tech making data do the same—with a little more success! Swapping pipettes for Python, I’ve realized that whether it’s molecules or machine learning models, the key is in the details (and sometimes in a good API). I believe that technology has the power to transform lives, and I’m excited to be part of that transformation as a Black professional in tech.
With expertise in Python, SQL, and a strong focus on AI engineering and machine learning (particularly in natural language processing and data science), I’ve developed a robust foundation in software development and data analysis. My hands-on experience, coupled with a research-driven mindset, positions me well for roles like machine learning scientist, AI engineer, or data scientist.
Beyond coding, I’m passionate about fitness, healthy eating, and exploring new places—whether it’s hiking a trail or immersing myself in a different culture while traveling. I’m always excited to continue learning, take on new challenges, and contribute to innovative projects that make an impact.
Let’s connect—I’d love to bring my technical skills and my energy to your next big idea.
· Enhanced System Efficiency: Spearheaded improvements in the backend infrastructure using Django, leading to a 15% reduction in API response time and a 20% improvement in system uptime through optimization of database queries and efficient use of Redis for caching.
• Integrated Machine Learning Models: Played a key role in integrating state- of-the-art natural language processing (NLP) models into Artheart.ai's production environment, increasing model inference speed by 25% with optimized GPU utilization.
• Django Expertise: Developed and maintained core Django applications, including custom APIs for the company's image generation service, improving overall API throughput by 30%. Additionally, built a highly reliable asynchronous task queue using Django and Celery, reducing task processing time by 40%.
• AI-Powered Search Functionality: Collaborated on implementing AI-enhanced search features using Meilisearch, improving content retrieval accuracy and user engagement metrics by 18%.
• Cross-Functional Collaboration: Worked closely with machine learning engineers and DevOps teams to ensure smooth deployment of AI models, and improved the scalability of services by transitioning to a containerized infrastructure on Google Kubernetes Engine (GKE).
• Impact on Business KPIs: Contributed to a 12% increase in user engagement through the successful deployment of AI-powered features and optimized backend services.
US Citizen
Artificial Intelligence And Machine Learning
University of Texas At Austin, Austin, TX