Applied Machine Learning Engineer
Imagine this. You are working on a precision inertial sensor where even after control and conventional compensation, a small residual error remains. We want to find out how much of that error can genuinely be predicted and removed using machine learning.
As a Machine Learning Engineer, you will own that investigation. You will build learned compensation models, benchmark them against a strong classical baseline, and determine where ML delivers measurable value and where it does not. This is a hypothesis to test rigorously, not a predetermined solution.
At Destinus, we are revolutionizing the defense industry with cutting-edge Unmanned Aerial Vehicles (UAVs). Our innovative technologies are designed to meet the unique demands of modern defense operations, delivering unparalleled speed, precision, and cost effectiveness. Destinus partners with government agencies and defense organizations worldwide to provide advanced solutions for mission-critical operations, enabling a new era of efficiency and technological superiority. Join us in shaping the future of defense with groundbreaking aerospace innovations.
What You'll Do
- Build ML models that predict residual sensor error using observable signals including temperature, thermal gradients, quadrature amplitude, drive signals, and sensor diagnostics
- Define rigorous validation protocols across unseen thermal profiles and physical sensor units to demonstrate genuine generalisation
