Sunderland, England, UK · Open to work

Embedded systems engineer,
wired into the cloud.

MSc Embedded Systems & IoT from Newcastle University. I build real-time firmware, IoT pipelines, and AWS-native backends, ranging from PID control loops to serverless infrastructure.

About

I work at the boundary between hardware and cloud, where a sensor's signal becomes a data pipeline and a control loop becomes an infrastructure decision.

My background spans real-time C/C++ on microcontrollers and FPGAs, through to Python backends, CI/CD pipelines, and AWS cloud infrastructure, built during an MSc in Embedded Systems & IoT and a role as an Information Systems Engineer at Lumen Technologies.

Currently building a portfolio of IoT + AWS projects focused on smart grid and energy-transition applications, combining embedded sensing with serverless, event-driven cloud architecture.

374 B
PID CORE FLASH FOOTPRINT · CORTEX-M4
12 KB
INT8 ANOMALY MODEL · ON-DEVICE
0.989
ROC AUC · HELD-OUT TEST SPLIT

Projects

Currently building

Smart Grid Energy Monitor

IN PROGRESS

Target architecture: a simulated smart-meter fleet streaming to AWS IoT Core → Kinesis → Timestream, with a live dashboard and SNS anomaly alerting, deployed via Terraform. My target-sector flagship project — not yet at a public-repo stage.

What's built so far: · What's next:

AWS IoT CoreKinesisTimestreamTerraform
U1

PID Core (C99 Control Library)

SIMULATED + CI TESTED

Dependency-free C99 PID controller with anti-windup and a filtered derivative-on-measurement term, unit tested in CI against a DC motor simulator and cross-compiled unchanged for a Cortex-M target.

C99PID ControlEmbeddedCI/CD
→ github.com/arfaali-naikar/pid-core
U2

Edge AI Anomaly Detection

SIMULATED + CI TESTED

TinyML vibration/speed anomaly detector for motor control systems: autoencoder trained and evaluated end-to-end in CI, with an edge inference loop bench-tested on an Arduino Nano 33 BLE and retraining synced through AWS SageMaker.

Results are measured on simulated vibration data; the firmware has not been run against a real motor.

TensorFlow LiteSageMakerEdge ML
→ github.com/arfaali-naikar/edge-motor-anomaly
U3

FPGA Audio Signal Processing (FIR Filter)

BENCH TESTED

8-tap FIR audio filter for a DE1-SoC Cyclone V FPGA: codec init, serial-to-parallel conversion and filtering in VHDL, recovered from a 2024 coursework report and verified in GHDL simulation. The reconstructed top-level has not been re-verified on physical hardware.

VHDLFPGADSP
→ github.com/arfaali-naikar/fpga-fir-audio-filter
U4

Closed-Loop Motor Control (M2M + PID)

HARDWARE VALIDATED

Real-time DC motor speed regulation on Raspberry Pi using a PID algorithm with encoder feedback, holding a 2Hz target speed across multihomed LAN routing.

Raspberry PiPID ControlM2M
→ github.com/arfaali-naikar/closed-loop-motor-control-m2m-pid
Show all projects
U5

RSA-Based Multimedia Encryption

BENCH TESTED

RSA cryptography engine in MATLAB for secure text, image, audio and video transmission, using modular exponentiation and signal-distortion analysis under noisy channels.

MATLABCryptographySignal Processing
→ github.com/arfaali-naikar/rsa-multimedia-encryption

Skills

Embedded & Firmware

  • C/C++
  • VHDL
  • Real-Time Systems
Familiar with
  • UART
  • STM32

Cloud & AWS

  • S3
  • Terraform
  • Amplify
Familiar with
  • IoT Core
  • Lambda
  • DynamoDB

DevOps

  • Docker
  • Jenkins
  • GitHub Actions
  • Grafana
Familiar with
  • Kubernetes

Data & Backend

  • Python
  • Django
  • Flask
Familiar with
  • SQL
  • Power BI

Experience

OCT 2025 - PRESENT
Software Developer
RIZLABS, SUNDERLAND (PART-TIME)

Contributing to software development work alongside full-time employment, building on backend and systems experience from Lumen Technologies.

DEC 2023 - PRESENT
Advanced Customer Advisor
ROYAL MAIL, DOXFORD

Previously Operations Team Member, then Customer Experience Advisor. Customer-facing support in a high-volume operations environment.

OCT 2022 - SEP 2023
Information Systems Engineer
LUMEN TECHNOLOGIES, BENGALURU
  • Built backend systems and data pipelines with Python, Django and Flask.
  • Implemented CI/CD (Jenkins, Docker) and system automation with BMC Control-M.
  • Managed monitoring (Nagios, Grafana) and performed vulnerability/penetration testing.
AUG 2021 - JAN 2022
Student Intern, Embedded Systems & IoT
THINKCIRCUIT TECHNOLOGIES, BENGALURU

Designed and prototyped secure embedded systems for IoT projects, integrating hardware and software components.


AI Use

AI is a tool I use to build and ship faster, not a substitute for engineering. Across these projects, some portion of the code, including boilerplate, syntax, and scaffolding, is AI-generated or AI-assisted. But the architecture, the logic, the problem-solving, and the ideas behind each project are solely mine, and I hold the result to the same standard as if I'd written every line myself.

Learn more

I treat AI as a guiding tool and assistant, in the way I'd use a compiler, a linter, or a senior colleague to review a design. It speeds up execution, but it doesn't make the decisions. The design intent, the trade-offs, and the "why" behind how a system is built come from me first.

This site is a direct example: I'm an embedded systems engineer, not a visual designer, so the layout, styling and theme of this page were AI-generated. The projects it documents were not.