Help us make complex human movement measurable

You will own, maintain, and evolve our production ESP32 firmware, ensuring it remains stable, secure, power-efficient, and recoverable in the field as new capabilities are introduced. The wearable currently relies on Wi-Fi for connectivity and includes Bluetooth functionality that needs to be assessed and extended into a secure mobile onboarding flow for transferring Wi-Fi credentials. Firmware will be your primary area of expertise, but you will also help scale our existing backend and cloud infrastructure. We care more about technical depth, learning ability, and excellent engineering than a conventional career path; relevant experience may come from industry, doctoral research, advanced university projects, or substantial independent work.

• Maintain production releases, OTA updates and rollback, watchdogs, crash recovery, memory and stack health, automated tests, and field diagnostics.
• Design, implement, test, and release secure mobile-to-device onboarding, including pairing or proof-of-possession, encrypted credential transfer over BLE, secure NVS storage, factory reset, and recovery flows.
• Build a simple iOS and Android onboarding app with clear progress, retry, and recovery flows, accounting for platform-specific BLE behaviour.
• Assess and extend the existing Bluetooth functionality for reliable mobile onboarding while protecting real-time IMU processing, firmware stability, and BLE/Wi-Fi coexistence on the shared 2.4 GHz radio.
• Measure and optimize battery use through sleep modes, radio duty cycling, CPU power management, and hardware power profiling.
• Make Wi-Fi and MQTT/TLS communication resilient to weak or intermittent connectivity through reconnection, buffering, backpressure, and offline synchronization.
• Contribute to scaling our existing backend services and cloud infrastructure, including APIs, device identity, observability, and operational reliability.
• Work with our data science team to evaluate and deploy suitable signal-processing or machine-learning workloads on-device, balancing accuracy, latency, memory, connectivity, and battery life.
• Validate new capabilities through long-running soak tests, battery-impact measurements, testing across phone models, and automated hardware-in-the-loop testing.

• Strong embedded C/C++ skills and hands-on experience with ESP32 and ESP-IDF.
• A solid command of FreeRTOS tasks, priorities, interrupts, watchdogs, queues, and concurrency.
• A strong understanding of BLE/GATT and the ability to design and rigorously test secure provisioning; prior shipped provisioning experience is valuable, but not required.
• Practical knowledge of Wi-Fi station and AP modes, reconnection, roaming, and captive-portal limitations.
• The ability to reason about security, failure modes, recovery, memory constraints, timing, and power beyond just the happy path.
• Experience measuring or optimizing power in battery-operated embedded systems.
• Familiarity with MQTT, TLS, certificates, device authentication, and unreliable-network handling.
• Ability to build a simple provisioning app using Flutter, React Native, Swift, or Kotlin and account for iOS and Android BLE differences.
• The independence to own architecture and releases while communicating clearly with a small cross-functional team.
• Willingness to work beyond firmware, learn unfamiliar technologies quickly, and use AI-assisted development tools responsibly while maintaining strong testing, security, and reliability standards.

• Shipped BLE provisioning or a battery-powered ESP32 product.
• Used NimBLE, ESP-IDF provisioning, Otii, Joulescope, Nordic PPK, or similar tools.
• Worked with high-rate IMU streams, SPI sensor drivers, wearable devices, battery gauges, or charging systems.
• Experience with TinyML, model quantization, TensorFlow Lite Micro, ESP-DL, or deploying algorithms on resource-constrained microcontrollers.
• Implemented secure boot, flash encryption, fleet provisioning, or credential lifecycle management.
• Built embedded CI/CD, Python test automation, hardware-in-the-loop tests, or production-line tooling.
• Experience with AWS IoT, radio certification, or testing BLE across a wide range of phones.

You will own, operate, and evolve the production infrastructure behind Aiving’s connected wearables. You will scale our existing platform to support more customers, devices, data, and geographic regions without compromising reliability or visibility into its operation. You will also work hands-on with our production ESP32 firmware. We do not expect equal depth across cloud, backend, embedded, mobile, and data; we are looking for technical strength in one or more of these areas, sound systems thinking, and the ability to take ownership across boundaries.

• Own and evolve our production cloud infrastructure so it remains reliable, observable, cost-conscious, and ready to scale across customers, devices, sports, and regions.
• Build and operate backend services, APIs, databases, and event-driven systems that connect wearable devices with our applications and internal tools.
• Operate and scale our existing secure MQTT device connectivity, improving resilience through buffering, retries, idempotency, monitoring, and recovery from intermittent connectivity.
• Plan regional deployments that account for latency, service availability, data residency, and varied network conditions.
• Maintain and extend our ESP32 firmware, diagnose issues across the device-cloud boundary, and safely release changes through tested OTA and rollback processes.
• Introduce pragmatic infrastructure as code, CI/CD, automated testing, logging, metrics, alerting, backups, and incident-response practices.
• Design clear data models and reliable data flows that preserve data quality, security, and traceability from raw sensor data to product features.
• Where your strengths fit, build reproducible data pipelines and tooling that give data scientists fast, dependable access to analysis-ready datasets.

• Experience building and operating production cloud systems.
• Strong backend engineering skills, ideally in Python, and experience designing APIs, services, and asynchronous or event-driven workloads.
• Practical knowledge of SQL databases, data modelling, and the trade-offs involved in storing and processing time-series or sensor data.
• Experience with infrastructure as code, CI/CD, containers, monitoring, alerting, and production troubleshooting.
• A sound understanding of cloud security, access control, secrets, encryption, backups, and data protection.
• Hands-on embedded C/C++ experience and the ability to build, flash, debug, modify, test, and safely release changes to an existing ESP32/ESP-IDF and FreeRTOS codebase on physical hardware. You should be comfortable investigating issues involving concurrency, timing, memory, watchdogs, networking, and recovery.
• Familiarity with IoT communication patterns such as MQTT, TLS, device authentication, unreliable networks, and over-the-air updates.
• The ability to reason across firmware, networking, backend, and mobile boundaries, even where you are not yet a specialist.
• The independence to make pragmatic technical decisions and own systems from implementation through production operation.

• Operated secure MQTT infrastructure or another production IoT platform with connected-device fleets.
• Shipped or maintained ESP32/ESP-IDF, FreeRTOS, robotics, or other constrained and concurrent systems.
• Built BLE/GATT functionality, secure device provisioning, or a simple iOS or Android app that communicates with hardware.
• Built ETL or ELT pipelines, workflow orchestration, data-quality checks, or platforms supporting data science and machine-learning teams.
• Designed multi-region systems or regional deployments subject to data-residency, connectivity, or service-availability constraints.
• Worked with high-volume time-series, IMU, telemetry, or other sensor data.
• Improved the reliability, security, performance, or cost of a growing production platform.
• Worked effectively across firmware, backend, data, and product boundaries in a small team.

You will develop and improve algorithms that detect sport-specific movements and measure the metrics that matter to athletes and coaches. Your work will span the full applied data science cycle: understanding the movement, planning data collection, exploring and preparing sensor data, developing and validating methods, and working with the team to deploy them in our products. You will join an established team with existing data, algorithms, and development frameworks while bringing your own ideas and technical judgement.

• Develop, improve, and validate algorithms that detect movements and derive accurate performance metrics from IMU and other wearable sensor data.
• Use signal processing, statistical methods, machine learning, and domain knowledge according to what best fits the problem.
• Design data-collection and labelling approaches with athletes, coaches, and sport experts when existing data is not sufficient.
• Build robust evaluation methods and test performance across athletes, devices, sessions, movement styles, and real-world conditions.
• Turn promising analyses into efficient, testable implementations using our existing real-time algorithm frameworks.
• Investigate model and algorithm failures, understand their causes, and improve performance without overfitting to individual datasets.
• Communicate findings clearly through visualizations, concise analysis, and close collaboration with data science, engineering, product, and sport experts.
• Contribute to reproducible workflows, shared tools, documentation, and stronger data science practices across the team.

• Strong Python skills and practical experience with scientific computing, data analysis, and machine-learning tools.
• Experience applying signal processing, statistics, machine learning, or a combination of these to time-series data.
• The ability to design rigorous evaluations, choose meaningful metrics, and recognize leakage, bias, overfitting, and weak ground truth.
• The ability to move from exploratory analysis to clear, tested, maintainable implementations.
• A curious and methodical approach to ambiguous real-world data and difficult failure cases.
• The ability to work independently while reviewing ideas, results, and code constructively with an existing team.
• A degree in data science, engineering, computer science, physics, applied mathematics, biomechanics, or comparable practical experience.
• Clear written and spoken English.

• Worked with IMU data, wearable sensors, sensor fusion, activity recognition, or human movement analysis.
• Developed algorithms for biomechanics, sports performance, robotics, healthcare, or another physical-world domain.
• Taken an algorithm from research or prototyping into a real-time or production product.
• Experience with noisy labels, limited datasets, subject-independent validation, or field data collected outside controlled environments.
• Built data pipelines, experiment-tracking tools, or reproducible workflows for a data science team.
• Meaningful experience as an athlete, coach, or practitioner in a sport.

You will explore how wearable IMU data can detect key movements in a sport you know well, then help us understand whether that sport could become part of Aiving's product offering.

• Choose a sport where movement detection can create value for athletes or coaches
• Define the key movements, events, or patterns worth detecting
• Collect or work with IMU data from real sport-specific movements
• Build and evaluate detection methods together with our technical team
• Help shape how the result could become a real product extension

• Currently enrolled in a master's degree program
• Strong interest in IMU data, movement analysis, sports technology, biomechanics, data science, or machine learning
• A clear connection to a sport, ideally as an athlete, coach, or practitioner
• Ability to work independently and communicate clearly

• You can explain which movements matter in your sport and why
• You have access to athletes, coaches, training sessions, or sport-specific expertise
• You want your thesis to contribute to a product used by real athletes

You can propose a thesis topic or explore one with us. We are especially interested in ideas that can create practical value for athletes, coaches, teams, or sport organizations.

• Sports technology, wearable data, IMU analysis, biomechanics, data science, machine learning, or coaching tools
• Research questions with a clear link to real training or competition
• Projects that can become prototypes, product features, or new insights for athletes and coaches
• Collaboration with our technical and product team throughout the thesis

• Currently enrolled in a master's degree program
• Strong academic background in a relevant field
• Interest in sports technology and innovation
• Ability to turn an open question into a focused thesis project
• Strong analytical, technical, or product thinking

• You already have a clear thesis idea
• You can connect your topic to a real athlete, coach, team, or sport context
• You are comfortable working in a startup environment with practical constraints

We are interested in practical collaborations where each partner brings something specific: sport expertise, research capability, athlete access, product ideas, distribution, or technology.

• Research projects around wearable sensors, IMU analysis, biomechanics, or performance feedback
• Sport-specific pilots with athletes, coaches, clubs, or federations
• Product or technology collaborations with sports technology companies and brands
• Validation projects that connect real sport needs with measurable movement data

• A clear sport, research, product, or market opportunity
• Access to relevant expertise, athletes, teams, facilities, technology, or distribution
• Interest in building something practical, not only theoretical
• Open communication and a willingness to define a focused pilot together

• Partners who understand the key movements and feedback needs in their sport
• Companies or brands looking to extend their sport technology offering
• Research groups that want their work to reach real athletes and coaches

Internships at Aiving are practical and close to the product. Depending on your background, you could contribute to software, data, design, product, research, or business development.

• Work on real projects that directly impact our product and athletes
• Learn from experienced professionals in your field of interest
• Gain hands-on experience in a fast-growing sports tech startup
• Contribute to innovative solutions for athletes and coaches
• Flexible time frames depending on your study program and availability

• Enthusiasm for sports technology and innovation
• Willingness to learn and contribute to real projects
• Strong communication skills
• Ability to work independently and as part of a team