AI/ML Software Engineer | Versed in Computer Vision & Generative AI | Deep Learning Expert | Turning Concepts into Realities ✨
My name is Akimi, and I am an AI/ML Software Engineer, based in Silicon Valley. I am passionate about data-driven innovation to solve problems that people face on a daily bases.
As an AI/ML Engineer, I specialize in developing cutting-edge Machine Learning models and deploying scalable AI solutions. With expertise in Deep Learning, Computer Vision, and Generative AI, I am excited about solving complex problems through data-driven approaches. My projects involves building and optimizing models for real-world applications, leveraging frameworks like TensorFlow and PyTorch. Please check out my GitHub page where I built my ML models to solve various problems: https://github.com/akimi-yano.
I have also worked as a Software Engineer at Microsoft and start up called Finli, and I have integrated AI/ML functionalities to empower applications and solved distinct scalability challenges. I have also contributed to improving latency and QoS issues for consumer facing apps.
I am always eager to explore new advancements in AI, enhance model performance, and contribute to impactful projects. I am currently looking for roles to solve challenges related to Generative AI for image and video. Please feel free to message me and connect to discuss any future collaboration ideas :D
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• Microsoft Designer team: Worked on the Brand Kit feature. Integrated with AI technologies such as GPT and DallE to generate usersʼ brands such as logo image, fonts, colors and voice. Improved QoS metrics such as latency and success rate. React, JavaScript and TypeScript for frontend and C# for the backend. • Microsoft Teams, PowerPoint team: Worked on an AI Speaker Coach feature to help people improve their public speaking skills. Refactored codebase from legacy system to a React-based application. • Internal tool team - AI Project: Built an email-to-case conversion pipeline for the CRM platform using Machine Learning with Microsoft AI Builder. • Internal tool team: Designed and built a new rules engine for complex query evaluation on Microsoftʼs bulk order revenue processing CRM platform using Azure and Microsoft Power Automate.

• Promoted to paid position as an Assistant Instructor available to the top 1% of Coding Dojo students. • Taught and mentored 300+ students learning remotely through the Online Coding Bootcamp program across multiple tech stacks (Python Django, JavaScript MERN, Java Spring Boot).

• Migrated UI components of the React Native iOS/Android app for the Version 2 launch. • Updated legacy documentation with clear, actionable step-by-step commands for Docker, PostgreSQL database and TablePlus, improving development environment setup process for new engineers. Finli iOS & Android Finli: Powering Neighborhood Businesses

Real-time face recognition and text notification system using Raspberry Pi and Intel NCS 2. • Programmed Raspberry Pi to take live camera data and pass through a face detection/recognition model. • Trained and ran face detection/recognition model with Intel’s Movidius Neural Compute Stick 2 to speed up face detection/recognition by 200+%. • Leveraged Twilio and Amazon S3 to notify the user in real-time with a text and photo when unauthorized individuals appeared on the camera. Donut Alert with Raspberry Pi akimi-yano/iot_ml_project
World-map of predicted spread of confirmed cases and fatalities of COVID-19 in 180+ countries using machine learning. • Built and trained multiple Light Gradient Boosting Model (LGBM) with Python, Pandas, Numpy, Matplotlib, Seaborn, Kaggle dataset, and Jupyter Notebook to generate prediction data over the next 30 days. • Enabled real-time prediction of the spread of the virus by deploying Java backend service using serverless Azure Functions to provide application access. • Demonstrated accuracy of predictions through visual graphical comparison of real vs. predicted data using JavaScript, Mapbox GLJS, and Recharts. Coronavirus Forecast Center github.com/akimi-yano/coronavirus-prediction

• Shortened average supplier turnaround time (TAT) by 30% by evaluating performance through data analysis of task metadata such as end-to-end completion time and codified delay signals with Google Sheets functions. • Identified bottlenecks and presented actionable visualizations to key stakeholders on a monthly basis, leading to reduced operational overhead.

• Successfully drove 100% of company (2,000+ employees) to complete technology compliance training using Microsoft Excel functions to track company progress and following up via automated and manual processes. • Leveraged expertise to direct software / hardware engineers to comply with US and international regulations regarding hardware, software and technology.

United Nations, Various Companies
• Engaged with government institutions across multiple countries to evaluate impact for government-funded projects • Conducted Exploratory Data Analysis (EDA) on large datasets and derived critical insights through data visualization and numerical analysis *Below is a list of consultancy work experience: Monterey Bay International Trade Association (MBITA) Global Trade Graduate Assistant August 2017 - June 2018 (11 months) Monterey, California International Development Exchange Association (IDEA) Global Trade Graduate Assistant August 2017 - June 2018 (11 months) Monterey, California Ministry of Economy, Trade and Industry Trade and Investment Specialist Consultant August 2017 - May 2018 (10 months) United Nations Institute for Training and Research (UNITAR) Trade and Investment Impact Evaluation Consultant December 2016 - September 2017 (10 months) United Nations Conference on Trade and Development (UNCTAD) Trade and Investment Analyst Graduate Assistant April 2017 - July 2017 (4 months) Geneva Area, Switzerland College Living Experience Multilingual Trainer August 2015 - May 2016 (10 months) Monterey, CA USA Global Majority Trade and Development Graduate Assistant August 2015 - May 2016 (10 months) Monterey, CA USA Center for Social Impact Learning (CSIL) Impact Investing Sustainability Consultant August 2015 - May 2016 (10 months) Monterey, CA USA Eurasia Foundation of Central Asia Business Impact Evaluation Consultant March 2016 - April 2016 (2 months) Almaty, Kazakhstan (Remote) Partners In Health Business Development Consulting Graduate Assistant January 2016 - January 2016 (1 month) Kigali/Rwinkwavu, Rwanda Middlebury Institute of International Studies at Monterey Fundraising Officer June 2015 - August 2015 (3 months) Monterey, CA USA
Skills: Artificial Intelligence (AI) · Machine Learning · PyTorch · TensorFlow · Scikit-Learn · Data Science
Activities and societies: Python - Django, MySQL JavaScript - MongoDB, Express.js, React, Node.js Java - Spring, Spring Boot
In Progress - taking courses through UC Santa Cruz's Silicon Valley Extension program.
President, MIIS International Trade Association (MITA)
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Multilingual peer-to-peer video chat application with live speech-to-text translation. • Delivered seamless video chat experience through implementing WebRTC negotiation mechanism using Firestore database and JavaScript and React web application. • Empowered users to communicate through humanized face-to-face / audial interaction to overcome language barriers using real-time speech-to-text translation between 8 languages powered by Azure Speech Translation. ice candi - Multilingual Video Chat github.com/akimi-yano/multilingual-video-chat
• Machine learning / computer vision app counting how often a person blinks or whether they are sleepy from media files. • Applied computer vision techniques using Python, OpenCV, NumPy and numerical calculations of dots placed on facial features to determine whether users are winking, sleepy, blinking, etc. with 85% accuracy. • Designed interactive experience with Python and Django web app to display visual alerts and image signaling in response to triggered events, allowing users to experience CV technology through exciting UI output.Speech Translation. Face Labo - Interactive Computer Vision github.com/akimi-yano/ml_project
Analyzed data from Moon Board rock climbing training system, and identified the easiest Moon Board problems at each difficulty level using Python. Rock Climbing Training System Data Analysis