Haris Mahmood

AI Research Engineer

Islamabad, Pakistan

I build AI agents and the systems they run on. Most recently I was a founding AI engineer at Unify (YC W23), working on AI agents that companies onboarded like new employees. I built much of the platform under them, from the RAG pipeline that gave them a company's knowledge to the generative UI they acted through and their integrations with a company's own apps, and in 2026 led a ground-up redesign of Unify's open-source agent harness, with an agent mesh and a memory built for both memoization and generalisation. Before that I co-founded Ivy and led its source-to-source machine learning transpiler, which rewrote PyTorch models and libraries as working, readable TensorFlow and JAX, so a PyTorch model could run on Google's TPUs through JAX.

Now

I'm looking for my next role. Most of my work has been building agents and the systems around them: designing harnesses from the ground up, giving agents a company's own data to work with, and running them securely and reliably for real users. I'd happily keep doing that, and keep pushing how agents and their harnesses can improve on the job.

The harness work at Unify also left me thinking that much of what an agent learns belongs in its weights, so I've been spending time on post-training: reinforcement learning against rewards that can be checked, the environments that training needs, and continual learning without forgetting. The Research page says what draws me to it.

Experience

  1. Jan 2025 – Oct 2026

    Unify Founding AI Engineer

    A startup that built an observability and evaluation platform for LLM applications, then AI agents that companies onboarded like new employees.

    • Built much of the platform the agents ran on: the RAG pipeline that gave them a company's knowledge, the generative UI they acted through, and their integrations with a company's own apps.
    • Led a ground-up redesign of the open-source agent harness, with an agent mesh and a memory built for both memoization and generalisation. On Continual-ARC, a benchmark Unify was building to test continual learning, the new harness solved more puzzles than the old one and than OpenClaw, Hermes Agent, and Prime Agent.
    • Built the tables and dashboards through which teams explored millions of logged traces and evaluations in its observability and evaluation platform.

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  2. 2024 – Jan 2025

    Ivy Co-founder and CEO

    A Unify spin-out built around an open-source transpiler that rewrote machine learning code from one framework into another.

    • Led its source-to-source transpiler as technical lead. It rewrote PyTorch models and libraries as working, readable TensorFlow and JAX, so a team whose training platform was built on TensorFlow could adopt a model published in PyTorch as code its engineers could still edit.
    • Validated it on Hugging Face models and worked through Kornia until about 90% of its functions and classes transpiled, and Kornia's maintainers merged the integration.

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  3. Dec 2023 – Jun 2024

    Noetico Senior Data and AI Engineer

    Turning biomedical literature into a knowledge graph, and answering questions over it.

    • Extended a biomedical entity recogniser to new entity types by training it on its own misses, and linked what it found to the client's ontology of about 220,000 concepts.
    • Built an LLM agent that turned plain-English questions into queries over the knowledge graph.

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  4. Mar 2023 – Apr 2024

    Unify Machine Learning Research Engineer II

    Unify was then building Ivy, an open-source framework for transpiling machine learning code between frameworks.

    • Led the team building Ivy's graph tracer and transpiler, which recorded a model as a computation graph and rebuilt it in PyTorch, TensorFlow, JAX, or NumPy.
    • Extended the Ivy framework itself, its frontends, backends, and stateful API, so that converted PyTorch modules became trainable Keras models.

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  5. 2020 – Mar 2023

    CureMD Machine Learning Engineer

    A healthcare software company.

    • Built SmartRecruit with one other engineer, before large language models: it parsed resumes of any layout and scored each candidate against the job in 2–3 seconds, and CureMD went on to use it for its own hiring.
    • Designed how it read each page, with our own algorithms for headings, columns, and reading order and custom-trained detection and entity-recognition models, at over 90% accuracy.

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  6. Jul 2020 – Sep 2020

    N-ovative Health Technologies Embedded Developer

    A medical-device company, now Revive Medical Technologies, during the COVID-19 equipment shortage.

    • Designed the electronics and control system of a powered air-purifying respirator and worked on the software of the N-Saviour ventilator.

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Open source