Somesh Kale
Software Developer with more than 2 year experience in developing web and mobile applications. Expertise in solving complex problems with efficient solutions and helped around 100+ people.
Understanding of Data-structures, Algorithms and Design patterns. Good code analyzing and debugging skills.
various workshops for 200+ students, helping them learn software development technologies while developing desktop and mobile applications.
I enjoy being challenged and engaging with projects that require me to work outside my comfort and knowledge set, as continuing to learn new languages and development techniques are important to me.
Experience
Software Developement Engineer
Seattle, WA, United States
Ownership of onboarding 4 merchants to Amazon portal to make payments using Amazon Pay, setting up Payment Secure Channels and Adding unit and integration tests to prevent errors in gamma and production stages. Managed AWS services cost, saving $100 monthly.
Worked on reducing development efforts for acquirer plugin implementations by 4 weeks using web hooks and API development.
Worked in a team of 8 to launch Amazon Pay checkout V2 for web and mobile, collaborated and defined requirements with product & QA.
Resolved 20 high severity risks during 1 week of oncall which rotates every 2 months for Amazon Pay checkout/refund/decline services.
Worked on designing sandbox test environment configurations and testing multiple merchants integration with amazon pay wallet.
Skills: Amazon CloudWatch · AWS CloudFormation · Amazon Web Services (AWS) · AWS Lambda · Amazon S3 · Amazon Dynamodb · Java · SQL
Software Development Engineer
Seattle, WA, United States
Worked on developing new features for iOS and Android Workdocs applications allowing secure storage and access to documents on mobile devices. Implemented amazon federate secure login for iOS mobile and iPad devices.
Ownership of publishing new application versions on apple store and android store including beta testing for applications.
Amazon Web Services (AWS) · iOS Development · Android Development · Java · Design Patterns
Software Engineer Intern
Charlotte, NC, United States
Developed an iOS mobile and wearable application using Xcode that tracks the real-time longitudinal health of Alzheimer disease patients.
OPerformed predictive analysis on the dataset, helping caretakers to detect unusual activities of the patients with 90% accuracy.
Software Developer
Pune, MH, India
Developed a Car Driving Simulation for students to gain driving skills in mixed traffic environments with the real-time view of the car.
Implemented A* path finding algorithm to create different traffic scenarios. Reduced the render time on android devices by 20%.
Designed levels in Simulation, to experience driving in different conditions with VR support. Helped 100 students learn driving.
Projects
Expense Tracker
Expense Tracker allows user to track their incomes and expenses.
Classification of Objects
Classify images of bricks, balls or cylinders against a cluttered background using the pre-trained Alexnet model in fastai/pytorch. Model achieved 95% accuracy.
VR Medical and Learning Simulation
This VR simulation allow users to engage with Medical Learning and Training procedures, also help them respond to high pressure situations and learn to deal with it
Car Driving Simulation
Driving simulation to experience the real-time view of the car for people with zero driving experience. Available with VR connectivity which allows immersive experience in 360 view.
Smile Detection using OpenCV
Smile Detection detects if the person is smiling or not, it also detects whether the particular person’s eyes are open or not and creates bounding boxes around smile and eyes.
Zombie Cause
Zombie Cause is a 3D First person Shooter game build with unity3D engine. Zombies are attacking the graveyard and you're stuck between these zombies and have to survive.
Classification of pulsar stars
Classification of Pulsar stars uses various algorithms to predict whether the features provided by the users belongs to a Pulsar star or not.
Predicting House Sales using Regression
Predicting the approximate price of the property based on factors like sqft living, number of bedrooms, bathrooms etc.
Sales Optimizer using Machine Learning
Sales optimizer helps owner to suggest items which should be placed side by side so that the customer is more likely to buy the item placed next to it.
