Build the Future of Industrial Intelligence
We're a remote-first team obsessed with physics, machine learning, and making industrial operations smarter. If you think in equations and dream in data pipelines, we want to hear from you.
Who We Are
TwinEdge is building the operating system for industrial assets. We combine first-principles physics with edge ML to predict equipment failures before they happen. Our platform runs on everything from Raspberry Pis in pump stations to ruggedized gateways on cell towers. We're early-stage, ambitious, and solving hard problems at the intersection of industrial engineering and software.
Our Values
Physics First
We don't just throw data at neural networks. We start with thermodynamics, fluid mechanics, and electrical engineering. Our physics models encode domain expertise that makes ML actually work in industry.
Ship to the Edge
We believe intelligence belongs where the data is generated. Our software runs on ARM processors in harsh environments, not just in comfortable cloud data centers.
Radical Transparency
We're honest about being early-stage. No inflated metrics, no fake logos. We earn trust by building great software.
Remote by Design
We're 100% remote. No office. No "hybrid." We hire the best people regardless of where they live and trust them to do great work.
How We Work
Fully remote
Work from anywhere in the world
Async-first
We write things down, minimize meetings, respect deep work
Small team, big impact
Every person ships features that reach production
Open source friendly
We contribute back to the tools we use
What We're Looking For
Physics & ML Engineer
Remote · Full-time
You'll build the physics models and ML pipelines that power TwinEdge's predictive capabilities. This isn't a typical ML role — you'll need to understand pump curves, thermodynamic cycles, and bearing vibration signatures as much as you understand gradient descent.
What You'll Do:
- •Design physics-based models for industrial equipment (pumps, blowers, generators, compressors, battery banks)
- •Build hybrid ML pipelines that combine first-principles equations with data-driven anomaly detection
- •Optimize ONNX models for edge deployment (10-50ms inference on ARM)
- •Create feature engineering pipelines for time-series sensor data
- •Work with industrial customers to understand their equipment and failure modes
- •Contribute to our open-source ML library (twinbox-ml)
What You Bring:
- •Deep knowledge of classical physics/engineering (thermodynamics, fluid mechanics, vibration analysis, electrical systems)
- •Experience with ML for time-series data (anomaly detection, RUL prediction, classification)
- •Python proficiency (scikit-learn, PyTorch, ONNX, pandas, numpy)
- •Comfort with edge constraints (limited memory, CPU-only inference, intermittent connectivity)
- •Bonus: Experience with OPC UA, Modbus, or other industrial protocols
- •Bonus: Background in mechanical or electrical engineering
What You Don't Need:
- •A PhD (though it's welcome)
- •Experience in "industrial IoT" specifically — domain curiosity matters more than domain experience
- •To be in a specific timezone
Open Roles
Physics & ML Engineer
Remote · Full-time
Don't see a role that fits? We're always looking for exceptional people.
Send us a note at careers@twinedgeai.com with what you'd want to work on.
Interested?
We'd love to hear from you. Get in touch and let's talk about what we're building.