Jake Drew

Summary

Software Engineer with 4+ years experience in software engineering, data-driven optimisation, automation, and embedded systems. Expertise in Python, Rust, C/C++, and Java, with applied experience in parameter optimisation, automated data collection, and signal processing across Linux and embedded platforms.

Experience

Software Engineer - Symetrica Security Ltd

Apr. 2025 - Present | Southampton, UK

• VeriFinder - Handheld Radiation Detection [S100] [S200] [S300]
  • C / C++
  • Android / Java mobile application
  • AngularJS web interface for device configuration and data visualisation
  • C firmware for MSP430 battery management controller

Applications Engineer - Microchip Technology Inc.

June 2022 - March 2025 | Whiteley, UK

• maXTouch - Automotive / Industrial Touch Controller [maXTouch]
• Designed parameter optimisation pipeline in Python - robotic grid sampling (OptoFidelity) to collect spatial accuracy data, then automated calibration to minimise positional error across sensor configurations
• Built automated multi-touch test suite, reduced device characterisation from 1 day to 30 minutes (48x speedup)
• Python automation for Weiss environmental chamber (syncing sensor data with temperature/humidity profiles)
• Data analysis and visualisation using NumPy / Pandas / Matplotlib
• Redesigned capacitive finger jigs, improving touch detection sensitivity by 48%
• Rust driver for Raspberry Pi 4B; Rust on RP2040 with Assembly PIOs
• C# plugins for maXTouchStudio (VS2015/2022); C for dsPIC33C (QEI)
• Lead engineer: mXT2912TDATv5 (~16" product). Project engineer: Slider / Ultrawide / Standard platforms
• 2 Preliminary Patents. Pre-compliance CISPR emission testing
• Technical customer support, FAE support, customer training across India, Korea, China

Reservist - British Army

Oct. 2019 - Oct. 2023 | Swansea, UK

• Royal Monmouthshire Royal Engineers (Militia)
  • Mobilised for Op Rescript (Covid Support Force)
  • Passed Basic Training (Alpha/Bravo)
  • Passed Army Officer Selection Board Briefing

Education

Swansea University

Bachelor of Engineering in Electronic and Electrical Engineering | Sept. 2018 - June 2022

• 2:1 BEng in Electrical and Electronic Engineering
• "Designing a Smartwatch with Fitness Tracking Capabilities"
  [paper.pdf]

Abingdon School

A-Levels / GCSEs | Sept. 2013 - June 2018

• Sixth form House Prefect and Editor for the House Termly Newsletter
• Member of Abingdon Film Unit. Directed two short CGI films
• A-Levels: Maths, Physics, Economics. AS: Government and Politics
• GCSEs: 3 A*, 4x A (incl. Mandarin), B, and C

Projects

Tiny Tapeout - QEI (Quadrature Encoder Interface)

Verilog | Oct. 2025 - Nov 2025

• Verilog project to design a quadrature x4 decoder with 15-bit up/down count and last-step direction
• Part of Tiny Tapeout SKY 25b shuttle using sky130A PDK on ChipFoundry CC2511 MPW.
• Chip estimated to be delivered ~June 2026

Building a Smartwatch with Fitness Tracking Capabilities

Python, Rust, PCB | Sept. 2021 - May 2022

• Final year University project
• Developed and trained TensorFlow time series classification model for activity recognition, achieving 83% accuracy
• Implemented data collection and processing pipeline for training data using Python
• Designed custom PCB incorporating RP2040 microcontroller and multiple sensors
• Built embedded application in Rust for real-time inference on resource-constrained hardware

To design and build a smartwatch and compare with commercial alternatives

C++, PCB | Sept. 2017 - May 2018

• EPQ Project during A-Levels
• ATmega328 chipset, custom PCB programmed with C++ which resulted in an A grade

Divshot Static Showdown Hackathon 48Hr

Javascript, HTML/CSS, Firebase | February 2016

• Static front-end only hackathon, JavaScript instant messenger using Firebase

Koding Hackathon 48Hr - Team Lead

Python, Django, HTML/CSS | November 2014

• Python Django app which summarises Terms and Conditions into bullet points

Technical Skills

• Languages: Python (NumPy/Pandas/matplotlib), Rust, C, C#, C++, JavaScript, Assembly
• Quantitative: Parameter optimisation, signal processing, time-series classification (TensorFlow), automated data collection & analysis
• Hardware: AVR, ARM, PIC, Raspberry Pi's, Weiss Chamber, OptoFidelity
• Tools: Git, SVN, Linux (Digital Ocean/Raspberry Pi), Altium, Kicad, Jira, MATLAB, Blender

This page uses basic HTML because it works and Actix.rs server because it is speedy.