About TRAX
TRAX is building a new way to understand and improve human performance in surfing.
We combine hardware, software, and data to help surfers understand what is actually happening in a session, and how to improve. Our system sits at the intersection of onboard motion sensing, pressure-based measurement, video capture, mobile workflows, cloud infrastructure, and machine-learning-powered analysis. By turning raw movement and force into structured insight, TRAX gives surfers objective feedback on how they generate speed, execute turns, and transfer weight - bridging the gap between effort and progression.
We're still early. That means work is hands-on, cross-functional, and messy in all the best ways. We're looking for people who want to help build both the product and the technical foundation around our embedded and ML systems - not just one narrow slice of it.
About the role
As a Founding Platform & Product Infrastructure Engineer at TRAX, you'll build the systems that connect our hardware, apps, cloud infrastructure, and machine learning into a cohesive product.
This role sits at the centre of the platform - defining how data flows from device to user, how systems scale, and how internal tools enable the team to move quickly. You'll focus on designing and building reliable, end-to-end infrastructure, from raw sensor and video ingestion through to processed outputs, model integration, and user-facing experiences.
By combining backend engineering and infrastructure design you'll create the foundation that enables TRAX to deliver meaningful, real-time performance feedback in complex, real-world environments.
What You'll Do
- Architect and build the core platform systems underpinning TRAX's product and internal workflows
- Design scalable data pipelines for ingesting, storing, and processing video, sensor data, metadata, and model outputs
- Develop reliable upload, synchronisation, and processing flows across mobile apps, cloud services, and internal tools
- Build backend services, APIs, and asynchronous workflows supporting real-time and offline experiences
- Create internal tools for debugging, QA, annotation, and operations to keep the system running smoothly
- Help productionise ML systems, including model hosting, artifact tracking, and feedback loops
- Collaborate closely with embedded, firmware, and ML teams to translate device outputs into robust product systems
- Make pragmatic architectural decisions, balancing speed, reliability, and scalability
- Continuously improve system reliability, observability, security, and deployment workflows as the platform scales
- Leverage AI-assisted engineering tools to accelerate development while maintaining strong engineering judgment
What we're looking for
We're looking for someone who can operate as a highly leveraged builder across the platform layer of the company - someone who enjoys connecting systems, reducing chaos, and building infrastructure that makes the rest of the product possible.
Basic Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
- Several years of hands-on experience in backend, platform, or infrastructure engineering roles
- Strong software engineering skills and experience building production systems, APIs, and data pipelines
- Previous experience with cloud platforms/infrastructure (AWS, GCP) and distributed systems
- Experience working with databases (SQL, NoSQL), object storage, queues, and asynchronous processing systems
- Ability to operate in ambiguity and create structure where none exists yet
Preferred Skills & Experience
- Experience working with video pipelines and/or high-frequency sensor data
- Experience designing and implementing robust upload/sync flows for mobile or IoT devices
- Previous work with mobile-adjacent workflows (uploads, retries, session handling, user data flows)
- Familiarity with ML model serving, inference pipelines, and productionising ML systems
- Familiarity with observability tooling, logging, and debugging distributed systems
- Experience with containerisation and deployment workflows (Docker, CI/CD)
Compensation & Benefits
- Competitive salary package
- Meaningful equity incentives
- Flexible remote work arrangements
- Time in the water (surfing helps us build and test the product)
- Tight-knit, fast-moving team with high ownership and low ego
- Opportunity to shape the company, culture, and systems from day one