Location: Remote, US-based
Contract: Full-Time, Permanent
Salary: $116,000-$154,000
Start Date: Asap
KinaTrax’s mission is to provide professional and collegiate teams with game-changing insights about their most valuable asset: their athletes. We deliver research-grade markerless motion capture technology that allows teams to collect in-game biomechanical performance data on their athletes. KinaTrax camera systems are currently deployed in over 50 stadiums & labs across MLB, MiLB, & NCAA organizations – and expanding rapidly. Our comprehensive data capture & analysis tools are operationalized for daily use by players, GM’s, coaches, trainers, medical staff, and beyond. As the market leader in Major League Baseball, KinaTrax has established itself as a foundational part of the teams’ day-to-day strategy and decision-making machine. But we aren’t finished. We are constantly innovating and looking to recruit talented teammates to help us continue to revolutionize this space. Your contributions will focus on bringing the next generation of athlete performance data, across a variety of sports, to teams worldwide.
As a Backend Software Engineer at KinaTrax, you will design and build the core systems that power our data platform, from ingestion and processing of large-scale biomechanical datasets to delivering performant APIs and real-time data experiences.
This role is focused on backend architecture and distributed systems, with opportunities to contribute across the stack where needed. You will work closely with product, data science, and infrastructure teams to ensure reliable, scalable, and high-performance systems.
Design and implement scalable backend services for ingesting, processing, and serving large-scale biomechanical and motion capture data
Architect and optimize database systems for high-volume, time-series and relational datasets
Build and maintain performant, secure, and well-documented RESTful APIs for internal and client-facing applications
Optimize data pipelines for throughput, latency, and cost efficiency across cloud environments
Improve system reliability, observability, and fault tolerance across distributed systems
Develop and refine data storage, indexing, and retention strategies for large datasets
Collaborate with frontend and product teams to support data visualization and reporting tools
Contribute to infrastructure decisions including cloud architecture, scaling strategies, and deployment pipelines
Integrate and support hardware/software interfaces tied to motion capture systems and edge data collection
Identify and implement improvements that increase internal efficiency and data delivery performance
Core Requirements
Strong experience building backend systems in Ruby (Rails), Node.js, or similar
Deep understanding of database design and optimization (MySQL, PostgreSQL, or similar)
Experience designing and maintaining RESTful APIs at scale
Experience working with cloud platforms (AWS preferred; Azure/Cloudflare a plus)
Solid understanding of distributed systems, performance tuning, and scalability
Experience with caching, queues, and background processing (e.g., Redis, Sidekiq, etc.)
Proficiency with Git and modern development workflows
Strong problem-solving skills and ability to work in a collaborative environment
Nice to Have
Experience with large-scale data pipelines or streaming systems
Familiarity with time-series or high-frequency data systems
Experience with real-time systems or WebSocket architectures
Exposure to motion capture, biomechanics, or sports analytics
Experience contributing to full-stack applications (React, etc.)
Work on cutting-edge sports technology used at the highest levels of competition
Solve real-world distributed systems problems involving massive, high-frequency datasets
Direct impact on how professional teams make decisions about performance and health
Opportunity to help define the architecture of a rapidly growing data platform
Fully remote position
Occasional travel to company locations or client sites may be required
Extended periods of computer usage
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