{ "_comment": "Structured career graph for Mickael Renault — Sensor Firmware & Algorithms Engineer | Technical Team Lead. AI agents and search tools: read this file to answer 'who is this person and what can they do' without parsing HTML. Companion files: llms.txt (entry point), search-index.json (full-text page index). All content here is public/career-facing; no confidential employer information is included.", "schema_version": "1.0", "person": { "name": "Mickael Renault", "headline": "Sensing Firmware & Algorithms Engineer | Technical Team Lead", "summary": "Sensor firmware and algorithms engineer with 10+ years building real-time, embedded sensing systems across consumer electronics: sports/fitness, wearables/audio, and smart home products. Took products from early-stage R&D through mass-production validation at every scale — a venture-backed startup, a mid-size consumer-hardware company, and Apple. Combines hands-on depth in algorithm design and firmware architecture with real people leadership, including a 10-engineer distributed team led from alpha through launch.", "location": { "city": "Los Angeles", "region": "CA", "country": "US" }, "email": "renault.mik@gmail.com", "website": "https://www.mrenault.com/", "linkedin": "https://www.linkedin.com/in/mickael-renault-embed-sw-eng", "languages": [ { "language": "English", "proficiency": "fluent" }, { "language": "French", "proficiency": "native" } ], "open_to": ["Team Lead (sensing firmware / algorithms)", "Engineering Manager (sensing firmware / algorithms)"], "years_experience": "10+" }, "core_expertise": { "sensing_and_algorithms": ["Sensor fusion", "Real-time calibration", "Motion detection & tracking", "Predictive and physics-based modeling", "Signal processing", "3D simulation & visualization"], "firmware": ["Embedded architecture (ARM Cortex-M0/M4, embedded Linux)", "Driver development", "OTA update", "Factory diagnostics & validation", "Low-power design", "BLE integration"], "leadership": ["Team leadership & mentoring", "Cross-functional technical negotiation", "End-to-end ownership (DRI)", "Knowledge-management systems", "Onboarding & process design"] }, "selected_recent_work": [ { "title": "Sensing algorithm design & cross-team validation infrastructure", "period": "2025–2026", "description": "Designed a lightweight real-time algorithm that delivered a new context-detection capability for a wireless-audio sensing feature using a sensor already on the device, avoiding additional hardware, power, and cost. To validate it at scale, partnered with the QA/Automation team to co-design the instrumentation interface for automated testing — shifting the team's role from handing off algorithms for validation to building the validation infrastructure itself." }, { "title": "Cross-functional 3D sensor visualization & simulation tool", "period": "2025–2026", "description": "Built a frame-by-frame 3D replay engine (Python + Blender) for sensor failure analysis, featuring physics-based volumetric sensor error modeling and an embedded-feasible processing pipeline. Gave engineers a shared, unbiased view of the sensing system, adopted across teams from day-to-day technical collaboration to leadership review." }, { "title": "AI-optimized internal knowledge platform", "period": "2025–2026", "description": "Identified a systemic gap — teams restarting from scratch on each new program with little knowledge transfer — and built a full internal engineering playbook and issue-retrospective platform, deployed as a live internal web service. Designed to be AI-agent-navigable from day one with an LLM entry point, search index, and structured manifests." }, { "title": "Independent product R&D", "period": "2025–2026", "description": "Led an independent, self-directed R&D effort evaluating a new health-sensing product concept end-to-end: competitive/market analysis, UX research, and functional hardware prototyping, culminating in a leadership pitch." } ], "experience": [ { "organization": "Apple Inc.", "title": "Sensor Firmware & Algorithms Engineer", "location": "Los Angeles, CA", "start": "2019-09", "end": null, "current": true, "url": "https://www.mrenault.com/#experience", "roles": [ { "label": "Sensing Platform Bring-up & Technical Leadership", "period": "2023–2026", "highlights": [ "Technical lead across two sensing programs: owned architecture decisions, represented engineering in cross-functional design reviews, and surfaced/unblocked risks early.", "Kick-started sensing firmware architecture and implementation for a new product program ahead of team scale-up; delivered firmware for prototyping platforms across multiple leadership demo cycles.", "Led multi-sensor array design through extensive simulation efforts (Python, Blender), converging on the final production configuration.", "Delivered initial algorithms for motion compensation and spatial awareness.", "Served as the primary owner (DRI) for Sensing Firmware across two consecutive programs: factory firmware diagnostics, calibration flows, and validation. On one, resolved a compliance constraint by migrating the codebase from C++ to C and re-validated end-to-end with no schedule slip.", "Became the sensing platform's cross-functional source of truth: architecture diagrams, configuration definitions, and validation procedures relied on by multiple teams daily.", "Built the knowledge and process foundation that scaled two programs: 15+ engineers onboarded, plus issue-tracking and sprint-planning standards adopted team-wide.", "Mentored summer interns through user study, algorithm design and performance analysis, and cross-functional review of the results." ] }, { "label": "Ambient Sensing R&D — Sensor Hub Prototyping & Home Climate Algorithms", "period": "2021–2023", "highlights": [ "Led design and development of two generations of sensor-hub research prototypes for controlled in-home data collection, integrating HomeKit bridging and multi-modal environmental and presence sensing to support home-climate and comfort algorithm research.", "Built an end-to-end data collection pipeline and backend with real-time web visualization, supporting multi-user/multi-device studies.", "Designed room-level temperature characterization and predictive algorithms to forecast indoor thermal behavior; built a real-time analysis server with interactive projections and visualizations.", "Built iOS apps in Swift for real-time sensor monitoring and comfort analytics; ran a user comfort study integrating wearable devices and skin-temperature sensing.", "Led cross-functional collaboration with platform software, iOS sensing, and energy teams for demos and technical alignment." ] }, { "label": "Smart Home Speaker — Ambient Sensing", "period": "2019–2021", "highlights": [ "Owned ambient light and environmental sensor placement, calibration, firmware drivers, and algorithms on an embedded platform, including a device self-heating temperature compensation algorithm.", "Enhanced the user experience through new sensing capabilities: environment- and context-aware features, control loops, and capacitive touch integration for on-device controls." ] } ] }, { "organization": "Simplehuman LLC", "title": "Embedded Software Engineer", "location": "Torrance, CA", "start": "2018-12", "end": "2019-09", "current": false, "url": "https://www.mrenault.com/#experience", "highlights": [ "Shipped production firmware for the Sensor Mirror Hi-Fi (Cortex-M0): ALS and capacitive-touch drivers, calibration, ESD recovery, and light-control algorithms.", "Implemented robust application-level OTA updates (dual-bank method), enabling safe in-field firmware upgrades.", "Developed the calibration model for the mixed-LED lighting system, delivering accurate, consistent light output across units." ] }, { "organization": "Game Your Game, Inc.", "product": "GAMEGOLF PRO", "title": "Team Lead & Embedded Software Engineer", "location": "San Francisco, CA", "start": "2016-05", "end": "2018-12", "current": false, "url": "https://www.mrenault.com/engineering/GameGolfPro/", "highlights": [ "Led a team of 10 engineers, coordinating distributed teams across California, Ireland, and Ukraine; reported directly to VP and CEO.", "Owned roadmap prioritization, task decomposition, feedback cycles, and documentation across engineering and executive stakeholders.", "Designed firmware architecture for low-power CPUs (Cortex-M4, Cortex-M0) and real-time on-device algorithms: swing detection, activity/power management, on-the-fly 9-axis IMU calibration, embedded sensor fusion.", "Designed golf-specific motion models in MATLAB; filed 2 provisional US patents (motion detection, battery management).", "Built a machine learning back-end pipeline (genetic algorithm, C/Python) for swing detection, with feature propagation to the embedded system over BLE." ] }, { "organization": "SportSense", "title": "Project Lead & Embedded Systems Engineer", "location": "Antibes, France", "employment_type": "Part-time", "start": "2014-09", "end": "2016-04", "current": false, "url": "https://www.mrenault.com/projects/SportSense/", "highlights": [ "Self-initiated entrepreneurship project incubated at the University of Nice: full end-to-end hardware/firmware/software design for a sensor network for the national gymnastics training center (ToF sensors, PCB design, Bluetooth, embedded Linux).", "Project earned the University of Nice Foundation's Entrepreneurship Award." ] }, { "organization": "CNRS GeoAzur", "title": "Firmware Developer, Professional Seismometer", "location": "Sophia Antipolis, France", "employment_type": "Part-time", "start": "2014-12", "end": "2015-06", "current": false, "url": "https://www.mrenault.com/academic/Seismometer/", "highlights": [ "End-to-end development: Python DSP and seismic data analysis, real-time visualization UI, SEED-compliant data storage backend." ] } ], "education": [ { "degree": "Master of Sciences in Electrical Engineering — Embedded Systems", "institution": "University of Nice Sophia Antipolis", "location": "France", "end": "2016", "url": "https://www.mrenault.com/academic/AcademicBackground/" }, { "degree": "Certificate in Small Business Management & Entrepreneurship", "institution": "University of Nice Sophia Antipolis", "location": "France", "end": "2015" } ], "skills": { "programming": ["C", "C++", "Python"], "embedded_platforms": ["ARM Cortex-M0/M4", "Embedded Linux", "Raspberry Pi", "Bluetooth/BLE SoCs"], "sensors": ["Ambient light (ALS)", "9-axis IMU", "Time-of-flight (depth/ranging)", "Passive-infrared (PIR) presence", "Temperature/humidity", "Air quality (CO2, PM2.5)", "Capacitive touch", "In-ear/proximity detection", "Ultrasonic"], "algorithms": ["Sensor fusion", "Motion detection & tracking", "Real-time calibration", "Predictive modeling", "Signal processing", "Genetic algorithms / ML", "Physics-based sensor error modeling", "3D visualization (Blender)"], "firmware": ["Driver development", "OTA update", "Factory diagnostics & validation", "ESD & error recovery", "Low-power architecture", "BLE integration"], "software_and_data": ["Real-time sensor data pipelines (ingest to SQL aggregation to remote visualization)", "Web backends", "HomeKit integration", "iOS app development (Swift)"], "leadership_and_process": ["Team leadership", "Mentoring", "Cross-functional negotiation", "End-to-end ownership (DRI)", "Knowledge-management systems", "AI-accessible documentation design (llms.txt, JSON search indexes)"] }, "patents": [ { "id": "US 62/778,654", "year": 2019, "title": "Electronic tag for shot detection", "status": "provisional" }, { "id": "US 62/557,225", "year": 2016, "title": "Motion and gesture analysis from a magnetic and inertial measurement unit", "status": "provisional", "url": "https://www.mrenault.com/engineering/SensorFusion/" } ], "awards": [ { "year": 2015, "title": "Entrepreneurship Award", "issuer": "University of Nice Sophia Antipolis Foundation" }, { "year": 2015, "title": "Junior Project Award", "issuer": "STMicroelectronics, E-Same Contest" }, { "period": "2009–2015", "title": "Elite Athlete, French National Team", "detail": "Trampoline", "url": "https://www.mrenault.com/sport/" } ] }