About me

Hey there! I'm passionate about crafting AI/ML solutions that don't just work but truly make a difference. Whether it's diving deep into data to uncover actionable insights or building user-friendly GenAI tools, I'm all about turning complex tech into something that drives growth and enhances user experiences.

In my tech journey, I've worn many hats - from AI researcher to coding ninja to a team leader. I've built AI systems that serve millions, cooked up some cool patents along with a PhD, and even created GenAI interfaces that let you interact with your data like it's your buddy.

My secret sauce? A perfect blend of hands-on coding, big-picture thinking, and a knack for turning user needs into impactful solutions. I've got a sixth sense for what users really want, and I use my tech wizardry to turn those wishes into reality. I've tackled challenges for clients across the globe in Australia, the US, Indonesia, Hong Kong, and India, always with a focus on creating real, tangible value through AI.

If you're looking for someone who can turn your AI dreams into reality, let's chat! Check out my social links on the left - I promise I'm much more useful than this brief bio suggests.

What I love doing

  • LLM Applications

    Integrate LLM-powered features into your products and businesses.

  • Insight Generation

    Develop ML models to generate trends and actionable insights from your data.

  • Big Data Architecture

    Design architecures to move, store and understand data at scale.

  • Web Automation

    Develop AI-powered automation apps to extract web data at scale.

Daniel lewis
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Daniel lewis

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Resume

Take a look at my full CV or browse below for some highlights.

Experience

  1. Team Lead: Data and AI @ Canopus

    2022 — Present

    Lead a data team and technically implemented AI-powered global scale systems.

    Developed state-of-the-art ML models, including FlowFormer, to classify millions of data flows and generate key metrics on user experience.

    Successfully drove product trials and crafted data-driven solutions for major global operators.

    Architected data pipelines processing 5B+ daily events using Kafka, ClickHouse, Superset.

    Migrated ML/AI stack to Google Cloud Platform, implementing modern MLOps practices.

  2. Software Engineer: ML @ Canopus

    2019 — 2022

    Developed high-performance packet processing software in Golang, using microservices to analyze network KPIs with tools like gRPC and Prometheus.

    Designed and deployed end-to-end ML pipelines for real-time classification and anomaly detection, leveraging Scikit-Learn, PyTorch, and MLflow.

    Ensured data integrity and model reliability by implementing data quality checks, feature engineering pipelines, and ETL jobs with continuous monitoring.

  3. Research Engineer @ Telstra

    2019 - 2020

    Assessed feasibility of building predictive models to measure YouTube 4k performance using their network node datasets. Invited to present to the Telstra Data Science Group (150+).

  4. Research Engineer @ Cisco

    2018-2019

    Built a system to model and monitor encrypted carrier wifi-calling sessions in enterprise networks using time-series machine learning. The system secured the enterprise by blocking malicious traffic over secure tunnels other than wifi-calls.

Education

  1. Ph.D. in ML @ UNSW Sydney, Australia

    2018 — 2022

    Developed an AI-powered network monitoring platform that passively measures application performance in real-time and at scales of terabits per second. It has been deployed in the largest global network operators. The ground-breaking research led to multiple patents and several papers in top conferences around the world.

  2. B.E. (Hons.) @ BITS Pilani, India

    2014 — 2018

    Studied Computer Science with a focus in Machine Learning. Graduated in the top 2% of the batch with a CGPA of 9.4/10. Received the Institute Merit Scholarship.

My skills

  • Programming: Python, Go, Typescript
    90%
  • Data Science and Engineering
    90%
  • Machine Learning and MLOps
    90%
  • GenAI: LLM finetuning and RAGs
    80%
  • System Design and Architecture
    80%
  • Product Development and Solution Engineering
    70%

Blog

I (want to) write about my experiences and learnings on my personal blog at medium.

If you'd like to subscribe to weekly (ish) AI related content, you can head to my substack.