Duncan Moss

Duncan Moss Email and Phone Number

Machine Learning & Deep Learning | Realtime Analyitics @ MangoBoost
Duncan Moss's Location
Portland, Oregon, United States, United States
Duncan Moss's Contact Details

Duncan Moss phone numbers

About Duncan Moss

Duncan Moss is a Machine Learning & Deep Learning | Realtime Analyitics at MangoBoost. He possess expertise in c++, objective c, matlab, wilderness first aid, php and 4 more skills.

Duncan Moss's Current Company Details
MangoBoost

Mangoboost

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Machine Learning & Deep Learning | Realtime Analyitics
Duncan Moss Work Experience Details
  • Mangoboost
    Senior Staff Engineer
    Mangoboost Aug 2023 - Present
    Seattle, Washington, United States
  • Megh Computing, Inc.
    Principal Engineer
    Megh Computing, Inc. Feb 2022 - Aug 2023
    Oregon, United States
    Lead Architect for Megh's Deep Learning technologies.Continuous Model Training - Continuous training (CT) is a process of fine-tuning AI models with new data to keep them up-to-date and accurate. - CT is especially useful in dynamic environments where the underlying data distribution can change rapidly, such as in intrusion and fraud detection. - Megh's CT framework allows models to adapt to the environment quickly and dynamically, virtually eliminating false positives. Contextual Analytic Framework - Contextual analytics is a data analytics method that takes into account the setting in which data is generated, collected, and analyzed. - The goal of contextual analytics is to provide a more complete and accurate understanding of the data by considering the context in which it was created. - The result is a more nuanced understanding of the data that can help organizations make more informed decisions and take more effective action.Nimble Application Framework - Nimble is a fast and lightweight service-based framework for implementing CPU, GPU, and FPGA video analytics pipelines. - It is designed to scale from single edge camera deployments to larger cloud-based systems. - Nimble is highly configurable and can be partitioned into multiple containers. This provides customers with unparalleled flexibility in how their solution is deployed and ultimately the cost of the pipeline.FPGA Deep Learning Engine - The Deep Learning Engine (DLE) has been designed from the ground up for streaming inference. - It consists of a library of high performance, mixed precision DL primitives that are drop-in replacements for TensorFlow and PyTorch layers. - The DLE compiler directly parses TensorFlow and PyTorch models, creating an optimal DLE configuration. - The quantized layers flow is 100% compliant with the TensorFlow Quantization Specification with floating point fallback.
  • Megh Computing, Inc.
    Senior Hardware Engineer
    Megh Computing, Inc. Jul 2019 - Jan 2022
  • Intel Corporation
    Deep Learning Hardware/Software Engineer
    Intel Corporation Jul 2018 - Jul 2019
    United States
    Working as a Deep Learning Engineer in the Deep Learning Accelerator Team.
  • University Of Sydney
    Research Engineer
    University Of Sydney Feb 2018 - May 2018
    Sydney, Australia
    High Frequency Signal Analysis using Dedicated Hardware
  • Intel Corporation
    Hardware Engineer Intern
    Intel Corporation May 2016 - Apr 2017
    Hillsboro, Oregon
    Developed machine learning workloads for the Xeon+FPGA
  • University Of Sydney
    Embedded Developer
    University Of Sydney Aug 2014 - Aug 2015
    Sydney, Australia
    - Constructed lightweight GPS and proximity devices for animal tracking and interaction studies. - Aided researchers by applying machine learning techniques to gain a richer understanding of animal behaviour.
  • University Of Sydney
    Lab Technician
    University Of Sydney Aug 2013 - Nov 2014
    Sydney, Australia
    Developed and deployed a thermal transfer laboratory for remote teaching in high school classrooms.
  • Nicta
    Summer Student
    Nicta Dec 2011 - Feb 2012
    Anzac Pde
    - Creating an infrastructure for Co-Verification between an S2E Virtual Machine and a SystemC Testbench.- Research into SystemC and how various Testbenches are implemented as well as the S2E Virtual Machine and examining symbolic execution.- Collaboration with colleges on the progress, direction and state of the project.
  • Knox Grammar School
    Orienteering Master In Charge
    Knox Grammar School 2009 - 2012
    I was responsible for the safety and enjoyment of the 50 students, as well as the 3 coaches who assisted me in running the sport.Managed and organised all in-school orienteering events that the students participated in.Communicated with the parents about the progress that their son was making, as well as any administration issues.Managed a team of coaches to ensure that the students were looked after and any problems are deal with swiftly.
  • Macquarie Group
    Summer Student
    Macquarie Group Jan 2011 - Feb 2011
    1 Martin Place
    As a student in Computer Engineering I was given computer related tasks, as well as some administration tasks. These were: - Developing a maths parser using ANTLR in C++, which included a Python interface. This was developed using the boost.python package. - Research and presentation of findings on the application of Haskell language to the specification and valuation of financial derivatives. - Electronically capturing, organising and archiving the paper copies of all Macquarie's official derivatives model Approvals.
  • Legg Software
    Programmer
    Legg Software Jul 2009 - Jan 2011
    I assisted in the ongoing refinement of the St John’s Granville web-based Event Manager. This web service provided an interface where the volunteers could sign up and register inventory that would be used at specific events. This job involved: - Using HTLM and PHP to create several small modules for the Event Manager that revolved around the organisation of events and the logging of inventory. - Assisted in the creation and maintenance of a LAMP based web server on which the Event Manager was hosted.

Duncan Moss Skills

C++ Objective C Matlab Wilderness First Aid Php Html Mobile Applications Mobile Devices Python

Duncan Moss Education Details

Frequently Asked Questions about Duncan Moss

What company does Duncan Moss work for?

Duncan Moss works for Mangoboost

What is Duncan Moss's role at the current company?

Duncan Moss's current role is Machine Learning & Deep Learning | Realtime Analyitics.

What is Duncan Moss's direct phone number?

Duncan Moss's direct phone number is +614029*****

What schools did Duncan Moss attend?

Duncan Moss attended University Of Sydney, University Of Sydney, Knox Grammar School.

What skills is Duncan Moss known for?

Duncan Moss has skills like C++, Objective C, Matlab, Wilderness First Aid, Php, Html, Mobile Applications, Mobile Devices, Python.

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