
Tushar Shetty
@tusharshetty
I build production AI platforms, computer vision systems, and scalable machine learning infrastructure.
What I'm looking for
At ABBYY, I’m architecting an AI Platform for the ML team from the ground up, creating the infrastructure backbone for scalable model development and deployment.
I build end-to-end Azure ML pipelines, production backend services, and containerised ML workflows using Docker and Kubernetes. I’ve also developed zero-shot document-processing evaluation, auto-labelling, fine-tuning, reinforcement-learning post-training, and observability capabilities.
Previously at Slamdunk.ai, I led machine-learning development for an AI-powered sports coaching app, growing its user base by 200% in six months. I processed over 100,000 video clips to achieve 98% movement-detection accuracy and reduced inference latency tenfold.
I contribute to vLLM, teach computer vision and mobile development, and build engineering communities. I care about scalable, meaningful technology and sharing knowledge with other engineers.
Experience
Work history, roles, and key accomplishments
Senior Software Engineer - AI Platform
ABBY
Mar 2025 - Present (1 year 6 months)
Architecting the AI Platform for ABBYY's ML team from the ground up, establishing the infrastructure backbone for scalable model development and deployment. Engineered end-to-end Azure ML pipelines and led production deployment of backend services.
AI/ML Engineer
Slamdunk.ai
Jan 2023 - Jan 2025 (2 years)
Led end-to-end Machine Learning development of Slamdunk, an AI-powered sports coaching app, implementing computer vision workflows for real-time form analysis and personalized training. Optimized model performance through transfer learning and big data training, processing over 100,000 video clips to achieve 98% accuracy in movement detection.
Education
Degrees, certifications, and relevant coursework
PES University
Bachelor of Technology, Computer Science and Engineering
2019 - 2023
Grade: 8.68
Pursued a Bachelor of Technology in Computer Science and Engineering, achieving a CGPA of 8.68.
Availability
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Authorized to work in
Salary expectations
Social media
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