# Mohammed Affan > Software Engineer at dYdX Location: New York, New York, United States Profile: https://flows.cv/mohammedaffan I am a software engineer at Arena, an startup focusing on ML applications in the CPG and manufacturing space. I have a master's degree in computer science from NYU, where I developed a passion for machine learning and distributed systems. I am deeply passionate about harnessing my knowledge in Machine Learning and Cloud Computing to innovate and build cutting-edge, scalable products from the ground up, ensuring they deliver substantial value to customers. My drive is fueled in collaborative, diverse environments where I can continuously engage with new technologies and industry domains. I am particularly invigorated by the challenge of creating something entirely novel, aspiring to not only contribute significantly to my field. My ambition is to explore uncharted territories in computer science, applying my skills to forge new paths and achieve notable breakthroughs. ## Work Experience ### Software Engineer @ dYdX Jan 2024 – Jan 2024 | New York City Metropolitan Area • Led team to deliver affiliates features for the protocol, indexer and front-end • Redesigned revenue sharing mechanism at protocol to be transparently shared across multiple recipients • Implemented social features including username generation and leaderboards • Enabled Cosmwasm on dYdX and worked with 3rd parties to provide functionality for integrating their contracts ### Software Engineer @ Arena Jan 2022 – Jan 2024 | New York City Metropolitan Area • Tech lead for the promotions team, leading a team for 5 people comprised of engineers and machine learning scientists. • Extended the machine learning platform by creating a job execution service which increased number of jobs which can be run at a time by 10000%. • Data engineered and deployed several ML models giving personalized recommendations to millions of users in several countries • Re-engineered critical machine learning pipelines using AWS step functions which reduced time by 50% and cost by 90%. • Led effort to implement a pricing engine which uses reinforcement learning to update client prices for the customer. • Led effort and designed integration points with external partners along multiple channels. • Managed internal and external stakeholders to align on business outcomes and designed systems to achieve those outcomes. ### Software Development Engineer @ Amazon Jan 2020 – Jan 2022 | Seattle, Washington, United States • Worked for the Alexa for PC UWP app and another undisclosed Alexa application. • Developed and tested cloud solutions enabling the team to turn on/off app features remotely. • Led effort to completely revamp core orchestration of Alexa UWP app. Provided technical direction and overall designs which were reviewed and approved by five teams across two sub organizations. • Revamped the entire audio input mechanism for Alexa UWP app which led to decrease in User Perceived Latency (UPL) by up to 50%. • Designed and developed audio pipeline for a new Alexa application which multiple partners are going to utilize. • Mentored and evaluated intern to successful completion of project. ### Software Engineer Intern @ md.ai Jan 2020 – Jan 2020 | Greater New York City Area • Built features for machine learning model training, testing, and inference on the company's medical imaging AI platform. • Designed and developed the machine learning model deployment framework, allowing users to deploy models on the platform • Collaborated with partners to integrate their machine learning models with the AI platform. ### Graduate Teaching Assistant @ New York University Jan 2019 – Jan 2020 | Greater New York City Area ### Software Development Engineer Intern @ Amazon Jan 2019 – Jan 2019 | Greater Seattle Area Interned for the Alexa for PC team • Designed, developed and tested grouping of smart home devices and controlling those groups for the Alexa PC UWP app using C# and XAML. • Efficiently synced cloud data with the app and implemented CRUD operations. • Designed UI for the features and linked it with the logic using MVVM pattern to create a smooth user experience. • This feature was then subsequently released in production and used by millions of users ### Graduate Teaching Assistant @ New York University Jan 2019 – Jan 2019 | Greater New York City Area ### Graduate Research Assistant @ New York University Jan 2019 – Jan 2019 | Greater New York City Area ### Student Developer @ Google Summer of Code Jan 2017 – Jan 2017 | Remote Contributed to Theano, which is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. • Achieved a speedup of 40% on GEMM convolution implementations by implementing several optimizers and completely overhauling the outdated Meta-optimizer. • Developed and tested forward and backward passes for 2D and 3D grouped Convolutions. Each operation was implemented for both the CPU and GPU using Python, C++, CUDA and CUDNN. • Analyzed the source code/conventions of TensorFlow, Caffe and Torch to ensure maximum cross compatibility. • Implemented and tested 2D and 3D Separable Convolutions. • 17 pull requests, 180+ commits and 4000+ lines of code contributed. ## Education ### Master of Science - MS in Computer Science New York University Jan 2018 – Jan 2020 ### Bachelor’s Degree in Computer Science Dayananda Sagar College of Engineering, BANGALORE Jan 2014 – Jan 2018 ### Science JAIN College Jan 2012 – Jan 2014 ### High School Sri aurobindo memorial School Jan 2000 – Jan 2012 ## Contact & Social - LinkedIn: https://linkedin.com/in/mdaffan --- Source: https://flows.cv/mohammedaffan JSON Resume: https://flows.cv/mohammedaffan/resume.json Last updated: 2026-03-20