You will work with modern C/C++ standards, FreeRTOS, Embedded Linux, and ARM Cortex/RISC-V toolchains, using JTAG/SWD debug interfaces, oscilloscopes, and logic analysers. You will own firmware architecture, lead end-to-end development, and bridge hardware-software integration for next-generation connected devices at Giantplus Middleware Solutions UK Ltd.

You will work with C/C++, FreeRTOS, Embedded Linux, ARM Cortex/RISC-V toolchains, JTAG/SWD, Git, oscilloscopes, and logic analysers. You will own firmware architecture for real-time embedded systems that power next-generation connected devices.

C, microcontrollers (NXP, Onsemi, nRF, PIC, ARM, TI), CAN, LIN, SPI, UART, I2C, and BLE. You will lead the software engineering team designing and developing embedded software for automotive safety-critical systems, power actuators, and smart door handles.

Work with C++, ROS, OMPL, and simulation tools like AFSIM and NGTS to develop tactical autonomy software for unmanned platforms across air, land, sea, and space domains, enabling multi-agent coordination and mission planning.

Work with Python, PyTorch, Git, GANs, diffusion models, flow models, and hybrid quantum-classical neural networks. You will design and evaluate generative ML algorithms at an early-stage start-up developing full-stack quantum systems, partnering with clients to apply these algorithms to real-world problems on quantum hardware.

Apple★4.1 (14k)· London

You will work with Python, C, Swift, LLDB, GDB, and Instruments to build automation, CI/CD pipelines, and ML/AI systems for crash clustering and anomaly detection. The team triages crashes and panics across Apple’s OS stack, building intelligent tooling to root-cause failures and improve the stability of over 2 billion devices. You will partner with Software, Hardware, and Silicon Engineering teams to drive systemic issues to resolution.

This role involves designing and building low-level infrastructure, including database internals, distributed systems, storage engines, and AI data infrastructure for vector search and retrieval. You will work in C, C++, Rust, or Go on performance-critical systems. The focus is on developing core components from first principles rather than integrating existing technologies.

Work with C/C++, systemd, PipeWire, PulseAudio, Opus, hidraw, and libusb to build a production-ready Linux daemon that captures system audio, encodes it as Opus, and streams 64-byte HID packets to a custom USB HID device. The role requires porting an existing Windows listener to Debian Linux while achieving full functional, audio-quality, latency, and protocol parity.

You will work with modern C++ (C++14/17+), embedded systems, RTOS, Linux, protocols (CAN, SPI, I2C) and emulation platforms like QEMU. The Arene team builds a software development platform for software-defined vehicles, developing SDK components and abstraction layers to streamline automotive software delivery and enhance safety.

You will build Physical AI solutions for robotics and edge devices, integrating Google DeepMind Robotics models with Gemini 3 foundation models to create autonomous agents for industrial environments. You will work with Gemini Robotics-ER, the Gemini Enterprise Agent Platform, MuJoCo-Warp, Intrinsic Flowstate, ROS 2, Python, JAX, Flax, Optax, Google TPUs, NVIDIA GPUs, Vertex AI, and XLA. The role involves moving Physical AI from simulation to production-grade hardware at scale.

ByteDance★3.8 (238)· London

Work with Linux kernel, GPU, system interconnect software, NVIDIA/AMD/TPU stacks, CUDA, and NCCL. The System Technologies and Engineering team develops infrastructure system software for ByteDance’s data centers, collaborating with SRE and business lines to improve reliability, stability, and performance. Provide technical leadership for OS and kernel adaptation of new server shapes.

Machine Learning Engineer role at a company developing autonomous systems for air, land, and maritime platforms. Work with deep learning, computer vision, LiDAR, Python, C++, Rust, Docker, Kubernetes, and GPU clusters to deploy ML on real autonomous systems.

You will develop and evolve LLVM-based and custom compiler toolchains, using excellent C++ skills for performance-critical, hardware-aware compiler systems. This work optimises AI/ML and accelerator-driven workloads at a semiconductor and AI computing company building high-performance compute platforms.

You will work with the Hivemind Enterprise Autonomy SDK, writing modern C++ and intermediate Python to develop AI and autonomy applications for unmanned platforms across air, sea, land, and space. You will deploy Hivemind AI infrastructure at customer sites, integrate autonomy into vehicles, debug API issues, and provide technical training. You join Shield AI, a defense-tech company building autonomy software and aircraft, supporting operations worldwide.

You’ll develop embedded firmware in C and C++, using interfaces like SPI, I2C, USB, UART, RS232, RS485, Ethernet, and CAN-bus. The role involves designing and maintaining embedded system architectures for complex projects incorporating advanced robotic systems.

You will develop real-time object detection, multi-target tracking, and sensor fusion algorithms using Kalman filters, deep learning, and data from EO/IR cameras, radars, and IMUs. You will interpret sensor ICDs and deploy perception software on SWaP-constrained airborne platforms, collaborating with autonomy and integration teams for Hivemind-powered unmanned aircraft operating in contested environments.

Build and maintain high-fidelity simulation environments using Python, MATLAB/Simulink, C++, and tools like CFD, FEA, and HITL. As part of Helsing’s Physical Products team, you will model vehicle dynamics, aerodynamics, and engagement-level behavior to de-risk design and validate against real test data for defence platforms.

Work with C++, real-time embedded systems, OOP, PNT techniques, real-time operating systems, machine learning, and test-driven development. The company builds Machine Learning and Digital Twin solutions for aerospace and defence, focusing on GPS-free navigation and flight safety for uncrewed autonomous systems. You'll join a small, expert team.

Working on robot learning, VLA, and world models using modern deep learning and ML. This founding role at a UK Physical AI startup researches models enabling robots to understand, learn, and act in the real world, with experiments on real hardware. You’ll lead research direction as part of a small, highly technical founding team.

As a founding-stage ML engineer, you will train vision-language-action models and world models, working in Python with modern ML frameworks to build training and evaluation pipelines. You will deploy these models on real robotic hardware, covering the full ML loop from data infrastructure to hardware testing.

Work with Python, C/C++, TensorFlow, PyTorch, and Embedded Development Kits to support customers integrating Innatera's Spiking Neural Processor technology for ultra-efficient AI at the edge. Act as technical advisor, translating customer feedback into product improvements, and conducting workshops and design reviews.

Use SystemVerilog, UVM, and Python to verify complex silicon for next-generation AI compute hardware. Develop reusable testbenches, verification plans, functional coverage, and assertions while building automation and influencing verification methodology alongside architecture, RTL, and software teams.

Hudson River Trading★4.5 (2)· London

You will work with macOS, Apple Business, MDM (Jamf, Workspace One, Intune), AutoPkg, Munki, Bash/Python, and enterprise networking. As an endpoint engineer on Hudson River Trading’s Enterprise Technology team, you will solve macOS challenges and improve user experience across the firm, which builds sophisticated computing environments for algorithmic trading.

Faculty★0.0 (16)· London

Research Scientists execute technical research in AI safety, using Python with PyTorch to study and steer transformer-based LLMs via white-box and black-box interpretability techniques like mechanistic interpretability and steering vectors. They collaborate with senior scientists at Faculty, a company that builds and deploys human-centric AI for over 350 global clients.

You will design, build, and test embedded software for Pod’s EV charging hardware platforms, working with Embedded Linux (Yocto, device tree), C, C++, or Rust, and connectivity technologies like Thread, Matter, Wi‑Fi, Bluetooth, and cellular IoT. You will own features end-to-end and collaborate with hardware and electronics teams across the full product lifecycle. Pod is a leading UK EV charging provider powering over 5 million miles daily.