Embedded Software Engineer

Dotplot is developing a breast health monitoring tool that empowers women to perform accurate monthly breast self-checks at home. Our mobile app works alongside a handheld ultrasound device to guide users through the scan in real time using a 3D model of their chest. We simultaneously capture location specific images for analysis.

Our mission is to improve breast health awareness and support earlier detection of breast cancer through intuitive, user-friendly technology.

The role

We are looking for a driven, hands-on engineer to join our London-based core team. Your primary focus will be production-quality firmware in C, reliable ultrasound image transfer and integration of our Real-time Acquisition Intelligence Layer (RAIL) into the product. RAIL is Dotplot’s real-time ultrasound acquisition guidance system. It uses incoming ultrasound and positional data to provide intuitive on-screen and on-device cues, helping women achieve complete scan coverage and capture consistent, high-quality ultrasound images without requiring clinical scanning expertise.

This role owns the complete RAIL work package, from research through to benchmarking, prototyping and embedded implementation. You will work within Dotplot’s medical device development framework and collaborate with our founders, manufacturing partner, app developers and scientific and regulatory advisors.

What you will own

Firmware, integration and deployment

• Develop, test and maintain production-quality firmware in C, using C++ and Python where appropriate.
• Integrate ultrasound hardware, sensors, vendor firmware and SDKs; implement device control, guided workflows, image-quality assessment and robust fault handling.
• Design reliable device-to-iOS communication in order that ultrasound images and metadata transfer completely, with validation, retry, reconnection and recovery mechanisms.
• Build diagnostics, logging, unit, integration and hardware-in-the-loop tests, with requirements, design records, test evidence and traceability suitable for a regulated medical device.
• Work with our manufacturing partner on firmware optimisation, technical risks, lead-time implications, and the pathway from prototype to deployable hardware.

You will work alongside a Machine Learning Lead to:

• Establish RAIL governance, milestones, technical risk tracking, secure dataset access and reproducible experiment controls for Dotplot’s annotated 799-image lay-user ultrasound dataset and acquisition metadata.
• Conduct a focused state-of-the-art review covering operator variability and distribution shift, closed-loop acquisition, multimodal fusion with noisy 3D position data, and robust training and uncertainty methods.
• Formally characterise RAIL’s novelty across three claims: jointly optimised closed-loop acquisition; dynamically weighted fusion of B-mode ultrasound and positional metadata; and training for operator-variable data distributions.
• Translate the research into implementable algorithms, prototypes and interfaces, then integrate approved acquisition-guidance components into the embedded workflow with appropriate performance and failure handling.
• Define benchmarks, comparators, validation metrics, reproducibility safeguards and Phase 2 thresholds; prepare expert reviews and secure documented RAIL.

• Strong hands-on commercial experience developing embedded firmware in C - typically around three years or more, or equivalent demonstrable capability.
• Proven experience writing software within a regulated medical - device lifecycle - or similar, including practical knowledge of IEC 62304, traceability and software contributions to ISO 14971 risk management.
• Experience integrating connected hardware, imaging systems, sensors, vendor SDKs or third-party firmware and moving a product from prototype toward production.
• Experience designing communication protocols, transferring large binary files or data streams reliably, and debugging across firmware, electronics and mobile-device interactions.
• Applied Python and algorithm-development experience, with the ability to evaluate technical literature, build reproducible prototypes, and translate research into production constraints.
• Clear technical writing and the confidence to work with manufacturers, advisors, investors and non-technical stakeholders.
• Ability to work from London 2-3 days each week and contribute actively to a small, founder-led team.

Helpful but not essential

• Ultrasound, medical imaging, computer vision, sensor fusion or other high-bandwidth sensing experience.
• On-device signal or image processing, objective image-quality assessment, active perception, or closed-loop control.
• Swift/Xcode integration, Azure-based data pipelines, connected-device cybersecurity, or telemetry.
• Evidence of mentoring others or the potential to lead an engineering capability as Dotplot grows.