About
Background, interests, education, and experience.
Tejas Mahajan is a software engineer specializing in large-scale data systems and the infrastructure that runs them, with a focus on production-grade data platforms and real-time backends for compute-heavy, latency-sensitive domains.
Currently at Nimble, I build the data and ML platform behind robot learning for an autonomous warehouse robotics company: streaming high-frequency sensor data off the robot fleet, turning it into reproducible training datasets for policy training, and developing the software that sets up and health-checks the stations that collect it. I also engineer the cost-aware pipelines and real-time services that turn fulfillment and fleet data into the operator-facing surfaces that run the warehouse floor.
Previously at MerQube, I architected the equity and options data ingestion systems and unified data access layers powering complex index computation workflows.
My background spans distributed systems, cloud-native infrastructure, and end-to-end ML deployment, from research-grade training and fine tuning deep learning models to deploying in resource constrained production systems.
I'm particularly interested in building intelligent, reliable systems at the intersection of data infrastructure, robot learning, and autonomous decision-making.