Krishna Desai

Software Engineer

Bengaluru South, Karnataka, India3 yrs 10 mos experience

AI EnabledHighly Stable

Key Highlights

Expert in cloud-native application development on AWS and Azure.
Co-author of a book on Confidential Computing.
Proven track record in AI and machine learning projects.

Stackforce AI infers this person is a Cloud Software Engineer with expertise in AI and machine learning for healthcare and real estate sectors.

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Skills

Core Skills

Cloud ComputingMicroservicesMachine LearningAiData Analysis

Other Skills

Python (Programming Language)Continuous Integration (CI)GolangRESTful APIsAWS S3GitHub ActionsPythonXGBoostLinear RegressionLogistic RegressionPandasNumPyKerasTensorFlowMatplotlib

About

Cloud Software Engineer with a strong commitment to delivering results. Known for quickly ramping up on unfamiliar tasks, embracing challenges with a proactive mindset, and consistently delivering high-quality outcomes. Recognized for unwavering dedication, ownership, and the ability to adapt and excel in dynamic environments. Demonstrated expertise in designing, developing, and deploying cloud-native applications on AWS and Microsoft Azure, with hands-on experience in orchestrating Docker containers using Kubernetes Strong believer in teamwork and collaboration — thrive in cross-functional environments where collective problem-solving and shared ownership drive success. Driven by a passion for leveraging data science and machine learning to develop innovative solutions to real-world challenges Co-author of the Book on Confidential Computing available at: https://www.amazon.com/dp/B0DK2Y4

Experience

3 yrs 10 mos

Total Experience

3 yrs 10 mos

Average Tenure

3 yrs 10 mos

Current Experience

Intel corporation

Cloud Software Development Engineer

Jul 2022 – Present · 3 yrs 10 mos · Bengaluru, Karnataka, India

Software Engineer – Golang | Microservices | CI/CD | Security | Cloud-Native
Developed Golang-based microservices and RESTful APIs to enable confidential computing through trust execution environment using containerized architectures.
Integrated PostgreSQL and Elasticsearch to ensure efficient, scalable data storage and querying.
Built messaging-enabled microservices and implemented secure AWS S3-based file upload/download functionality.
Maintained high code quality through extensive unit testing and continuous integration workflows.
Automated security CI pipelines using GitHub Actions, integrating tools like Protex, Coverity, Black Duck BDBA, and Trivy for vulnerability detection and compliance.
Migrated CI/CD pipelines to GitHub ARC on Kubernetes, improving pipeline security, scalability, and infrastructure efficiency.
Designed and automated OpenAPI documentation for seamless API consumption and developer onboarding.
Actively mentored junior engineers on clean architecture and design best practices.
Collaborated cross-functionally with frontend/backend developers, DevOps, QA, and tech writers to align on design, development, and delivery.

Python (Programming Language)Continuous Integration (CI)Cloud ComputingMicroservices

Medtronic

AI-ML Intern

Sep 2021 – Aug 2022 · 11 mos · Bengaluru, Karnataka, India · On-site

🔹 Defined and documented system requirements for a peritoneal dialysis machine, ensuring alignment with clinical workflows and regulatory compliance
🔹 Improved diagnostic accuracy by 15% through implementation of AI-based image classification models for cancer stage detection

Python (Programming Language)Machine LearningAI

Rubixe

Trainee

Aug 2020 – Dec 2020 · 4 mos · Bengaluru, Karnataka, India

🔹 House Price Prediction Model
Developed a predictive model using XGBoost Regressor and Linear Regression to assist clients in buying homes at optimal prices and identifying high-return features.
Technologies: Python, Scikit-Learn, XGBoost
🔹 Employee Performance Prediction
Built a model using Logistic Regression to forecast employees’ yearly performance and aid in performance management decisions.
Technologies: Python, Pandas, Scikit-Learn
🔹 Insurance Claim Data Analysis
Performed data cleaning, exploration, and feature selection on insurance claim datasets to uncover trends and reduce claim fraud risks.
Tools: Python, NumPy, Pandas, Matplotlib
🔹 Spare Parts Demand Forecasting
Implemented an LSTM (Long Short-Term Memory) neural network model for accurate forecasting of spare parts demand in inventory systems.
Technologies: Python, Keras, TensorFlow
🔹 COVID-19 Spread Prediction
Conducted time-series data analysis and modeling to predict the spread of COVID-19 using real-world datasets.
Technologies: Python, Pandas, Matplotlib, ARIMA