Inference Algorithm Engineer

About this vacancy
As an Inference Algorithm Engineer, you develop the algorithms and mathematical frameworks that enable high‑tech systems to extract structure, estimate states and reason under uncertainty in high‑dimensional environments. You work where applied physics, probabilistic modelling, numerical optimisation and machine learning intersect.

Responsibilities

Develop physics‑informed inference algorithms grounded in probability theory, system dynamics and measurement physics.

Build mathematical models describing complex physical systems, including noise processes, interactions and uncertainty mechanisms.

Design Bayesian estimation pipelines such as Kalman filtering variants, particle filters, variational inference or MCMC methods.

Prototype, validate and benchmark algorithms through simulation and experimental setups.

Translate theoretical models into efficient, scalable and real‑time capable implementations.

Collaborate with sensing specialists, physicists, embedded software engineers, control experts and system architects to integrate inference algorithms end‑to‑end.

Perform sensitivity studies, robustness analysis and uncertainty propagation assessments across physical models.

Explore new physics‑informed inference methodologies and identify opportunities for performance breakthroughs.

Present clear, well‑founded algorithmic decisions and guide multidisciplinary teams in selecting the right inference approach.

#J-18808-Ljbffr