Pranav Prajapati
@pranavprajapati
GenAI and Machine Learning Engineer building enterprise software intelligence.
What I'm looking for
I’m a GenAI and Machine Learning Engineer focused on turning complex, multi-platform data into accurate, actionable software intelligence. I correlate signals across tools like GitHub, Jira, and Jenkins using embeddings and knowledge graphs to support measurable productivity outcomes (e.g., DORA, SPACE).
At Truxt, I build application and chat-interface harnesses to integrate with tools like openclaw and nemoclaw, and I optimize GenAI performance by caching prompts on VertexAI to reduce both cost and latency. I also integrate enterprise-grade MCP servers (mcp-toolbox, context7) to improve context quality and answer accuracy.
Previously, as a Core-Developer for GSoC, I helped shape future road-maps and maintain sktime by scaling backends for Polars support, maintaining forecasting models on Hugging Face, and implementing the MOIRAI foundation model to enable complex transformer-based time-series modeling through a simple interface. I also contribute as an Open Source Developer—extending Keras ecosystems, migrating architectures for Keras3 compatibility, and shipping open solutions through hackathons and volunteer work.
Experience
Work history, roles, and key accomplishments
GenAI and Machine Learning Engineer
Truxt
Nov 2024 - Present (1 year 6 months)
Correlates signals across GitHub, Jira, and Jenkins using embeddings and knowledge graphs to deliver software intelligence and productivity metrics (DORA, SPACE). Builds GenAI harnesses integrating OpenClaw and NemocLaw tools and uses Vertex AI prompt caching plus enterprise MCP servers for more accurate answers.
Core Developer (GSoC)
Sktime
May 2024 - Present (2 years)
Helps set sktime roadmap, reviews PRs daily, and maintains project development on GitHub. Scaled time-series backends by adding Polars DataFrame support and implemented MOIRAI foundation models with PEFT/LoRA adapter workflows for fine-tuning.
Open Source Developer (Volunteer)
Keras and Keras-NLP
Aug 2023 - Jan 2024 (5 months)
Contributed to Keras-NLP by adding Google ELECTRA pretrained model weights to the Keras ecosystem, converting PyTorch weights to Keras-compatible format. Migrated VGG architectures in Keras-CV from Keras 2 to Keras 3 and maintained Keras example notebooks for latest-version compatibility.
Education
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Pranav hasn't added their education
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