TinyML Engineer | Deep R&D Tech Robotics Hyperscaler | London

AI Futures
London, GB
On-site

Why this role

Pace
Fast Paced
Collaboration
Medium
Autonomy
Medium
Decision Impact
Team
Role Level
Individual Contributor

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • design, deploy & optimize TinyML models on microcontrollers
  • develop real-time sensing and control pipelines
  • apply advanced optimization techniques
Typical background
Embedded ML / TinyML experienceStrong background in C/C++, Python, & microcontroller platforms

Transferable backgrounds

  • Coming from TinyML
  • Coming from embedded systems
  • Coming from microcontroller platforms

Skills & requirements

Required

TinymlC/c++PythonMicrocontroller PlatformsCmsis-nnTensorflow LiteEdge ImpulseMicrocontrollers

Preferred

ARM Cortex-mRisc-vCustom AcceleratorsStm32Esp32Nordic Platforms

Stack & domain

TinymlC/c++PythonMicrocontroller PlatformsCmsis-nnTensorflow LiteEdge ImpulseStm32Esp32Nordic PlatformsMachine LearningDeep Learning ArchitecturesCommunicationAutonomous SystemsPhysical World IntelligenceEmbedded SystemsReal-time Sensing And Control Pipelines

About the role

Original posting from AI Futures

AI Futures are partnered exclusively with the most exciting AI startup in Germany on a Search for a Tiny ML Engineer

This is a once in a lifetime opportunity to create a new industry by building the operating system for physical world intelligence. Funded by Tier 1 VCs the company are developing a new category of autonomous systems capable of delivering low-signature, persistent intelligence at scale, creating a programmable layer that connects the physical world to organisations and turns deployments into real insight. With initial applications in defence and long-term applications across security, infrastructure and industry, the company is scaling from 50 to 200 people in 2026.

The Role:

  • Design, deploy & optimize TinyML models on microcontrollers (ARM Cortex-M, RISC-V, custom accelerators) used on living insect biobot systems
  • Hands on Implementation experience of TinyML on MCU's
  • Developing real-time sensing and control pipelines
  • Applying advanced optimisation techniques (quantisation, pruning, compression)
  • Integrating ML models with advanced embedded systems
  • Shaping the company’s next generation of intelligent edge platforms

The Candidate:

  • Embedded ML / TinyML experience
  • Strong background in C/C++, Python, & microcontroller platforms
  • Experience with CMSIS-NN, Tensorflow lite, Edge Impulse
  • Background with microcontrollers such as STM32, ESP32, or Nordic platforms
  • Strong understanding of machine learning and deep learning architectures
  • Fluent English

This is an opportunity to get in at the perfect time, work on one of the most technically ambitious AI deployments ever, learn from a team of A Players and exited founders, grow with the company and get equity.

Source: AI Futures careers

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