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  • Staff Engineer, Scale AI

Prassanna Ravishankar

Staff engineer building infrastructure for AI agents. Writes about agents, ML systems and MLOps.

I am a Machine Learning Engineer focused on the intersection of infrastructure, data, and modelling. My work revolves around building robust systems that enable the "Agentic Web," where AI agents can reliably operate, communicate, and execute complex workflows.

Currently, I'm simplifying the unification of Code and AI, designing protocols that allow agents to be more than just chat bots.

experience

    • 2025-05 to now
    • London, U.K.

    Staff Engineer, Scale AI

    • 2023-01 to 2025-05
    • London, U.K.

    Principal MLOps Engineer + Platforms Team Lead, Papercup AI

    • Designed and led the ML cloud training stack from scratch with ClearML and Skypilot, scaling compute from 16 to 50 GPUs.
    • Led an initiative to migrate the model serving stack to be serverless, reducing idle cost time by 90%. Built an internal library to create consistent interfaces, conventions and OpenTelemetry tracing.
    • Designed and led an initiative to increase data processing speeds by 50x using Apache Beam with GCP's Dataflow using 250+ GPUs.
    • Implemented a tool using GPT-4 and LangChain to automate creative text generation, reducing data acquisition time from ~4 months to ~2 weeks.
    • Automated and productionized a transcription and translation workflow using Deepgram, GPT-4, LangChain, Temporal, FastAPI and Streamlit, allowing the asynchronous system to serve 1000% more workflows per day.
    • Created the foundational Platforms team (SREs, MLOps, Data Engineers) and hired two MLOps engineers to the team.
    • 2020-10 to 2023-01
    • Belfast, U.K.

    Senior Machine Learning Engineer, Zenith AI (Acquired by Opentrons)

    • Founding engineering team member, company acquired after 9 months.
    • Reduced cumulative QA build time from 2800 minutes to 200 minutes per week by optimizing Docker builds.
    • Designed an async queue-based graph executor reducing ML load time from 3 hours to 35 minutes.
    • Led a team implementing secure self-service ML web app deployments, cutting wait times from 3 days to 15 minutes.
    • 2019-09 to 2020-10
    • Belfast, U.K.

    Applied Computer Vision Researcher, AnyVision (Now Oosto)

    • Developed a Focus of Attention system for retail using 3D geometry and depth estimation.
    • Built a defect classification prototype in 48 hours, later piloted by a major electrical company.
    • Introduced a benchmark-driven-development research philosophy with Grafana analytics.
    • 2017-03 to 2019-09
    • Barcelona, Spain

    Image Processing Consultant @ HP, Altran (Acquired by Capgemini)

    • Supported the creation of a Python-based middleware for large format printers.
    • Implemented sensor-based calibration routines for large format and 3D printers.
    • Built internal tools to identify and fix calibration bugs, halving debugging time for R&D.

education

    • 2013-05 to 2017-02
    • Barcelona, Spain

    PhD Student and Teaching Assistant, Computer Vision Center

    Left in 2017 before completing the PhD. Implemented Slither, a random forest framework for semantic segmentation using C++ and Python.

    • 2011-09 to 2012-09
    • Sheffield, U.K.

    MSc. Computer Vision, University of Sheffield

    Worked on face recognition, traffic analysis, and FPGA-based cryptography.

    • 2007-08 to 2011-05
    • Manipal, India

    B.E. in Electronics and Communication, Manipal Institute of Technology

    Internships at FH Westkueste, Germany (2011) and mdirect, Tunisia (2009).

stack

languages Python, Terraform
frameworks PyTorch, Temporal, FastAPI, LangChain, Agent SDKs, OpenTelemetry, MCP, ONNX
tools Kubernetes, Docker, SkyPilot, AWS/GCP, Training Job Orchestration, Apache Beam, Dagster/Airflow