Abhijat Sarari

Built and deployed an AI-focused platform delivering intelligent automation and data-driven solutions. Designed and Integrated end-to-end ML pipelines, APIs, and cloud deployments using Python, Azure. Led architecture decisions, product roadmap, and hands-on development across AI, backend, and DevOps layers.

Developing scalable application features with a focus on performance optimization and system reliability. Collaborating with cross-functional teams to integrate AI-driven components into production systems.

Authored and published technical articles on AI, ML, APIs, and system design, contributing to developer education.

Microsoft Alpha Learn Student Ambassador: Directed 100+ valuable feedback points in alpha testing to improve Microsoft products. Conducted monthly Git and GitHub Copilot workshops with an average of 30 participants per session. Microsoft Beta Learn Student Ambassador: Engaged in beta testing, delivering feedback that led to a 20% increase in Microsoft software quality. Created informative content and tutorials, garnering 5,000+ views from beta testers and tech enthusiasts.

Effected timely and accurate assistance to students on complex financial concepts, helping over 200 students. Assisted students in resolving over 300 finance-related problems. Collaborated with a diverse network of students to enhance their comprehension of financial topics, contributing to a 20% increase in academic success.

Citi Bank System Engineer: Facilitated strategy for process automation for configuration management and managed across data lifecycle and capacity management to improve efficiency by 60%. Automated design optimizations to existing systems to cut expenses by 25%. Saved roughly $40K per year through widespread testing and system maintenance procedures. Royal Bank of Scotland System Engineer: Configure and maintain network services, including backup and recovery and maintaining web servers in Linux environment. Automate data collection activities to increase productivity (~60%). Influenced with migration of datacenter to cloud solutions (AWS & Azure). Provided support to 250+ users in Linux and Mac environments.

Refined 14+ facial expression datasets for media and entertainment applications, improving accuracy. Developed a Python web scraping program, downloading 10,000+ company descriptions and stock quotes, increasing research efficiency by 50%.

Trained and done hands-on experience in data science acceleration. Improve performance of hardware and software 70% better by adopting techniques of data acceleration.

Created 25+ other ML models and earn hands-on experience in CNN, RNN and other neural networks along with computer vision. Co-ordinated to TensorFlow, an open-source machine learning library, through design discussions, code reviews, and commits; implemented ~5,000 lines of code in 6 months.