Key Responsibilities:
Develop, train, and optimize ML models for localization and tracking.
Apply state-of-the-art ML techniques (e.g., transformers, probabilistic modeling) to localization challenges.
Collaborate with localization experts and software engineers for production deployment.
Conduct simulations to evaluate model performance and robustness.
Research and implement recent ML methods and best practices.
Maintain documentation of ML models, experiments, and components.
Analyze model failures and design improvement strategies.
Key Skills:
Solid understanding of ML algorithms, model training, evaluation, and deployment.
Background in signal processing and wireless technologies.
Proficiency in Python and ML frameworks (PyTorch).
Analytical and problem-solving skills with data-driven approaches.
Familiarity with software development best practices and ML deployment pipelines.
Ability to work independently and in teams.
Robust communication skills in English.
Preferred:
Experience with localization algorithms or sensor fusion.
Knowledge of probabilistic modeling and estimation theory.