AI Engineer, LIGHT

Mission

Utilize AI to improve the efficiency, energy consumption, and overall performance of lighting systems.
Leverage synthetic data generated from simulation tools to train and test AI models.
Develop AI models that can be easily generalized and parameterized to adapt to different lighting environments and applications.
Utilize AI techniques to automate or assist in the annotation of large datasets.
Contribute to the development of innovative AI solutions for lighting systems through research, development, and technical publications.

Responsibilities

AI-Driven Lighting Optimization: Employ AI techniques to improve the efficiency, energy consumption, and overall performance of lighting systems. Explore opportunities to enhance lighting control, automation, and user experience.
Synthetic Data Utilization: Leverage synthetic data generated from simulation tools to train and test AI models. This will enable more efficient and effective model development, especially in scenarios where real-world data is limited or difficult to obtain.
Model Generalization and Parameterization: Develop AI models that can be easily generalized and parameterized to adapt to different lighting environments and applications, and increase the flexibility and scalability of the solutions.
Large Dataset Annotation: Utilize AI techniques to automate or assist in the annotation of large datasets. This will streamline the data preparation process and enable more efficient model training.
Problem Formulation and Solution Design: Conduct in-depth research to understand and define problems related to lighting systems. Explore and evaluate AI-based algorithms and techniques that can effectively solve these problems. Identify strategies to integrate AI solutions into existing lighting applications.
AI Model Development: Create or modify scripts to establish training environments for AI models. Develop new use cases for simulation to enhance model performance. Experiment with different model parameters and environments to optimize training processes. Train and test models to evaluate their accuracy and effectiveness.
Data Analysis and Visualization: Analyze datasets to identify potential issues that may impact model accuracy and functionality. Develop insightful data visualizations using dashboards to facilitate data analysis and model evaluation.
Documentation and Communication: Document the entire workflow, including research findings, model development processes, and results. Prepare clear and concise presentations to effectively communicate technical concepts and project outcomes.
Technical Publications: Contribute to the publication of technical papers or patents when significant milestones are achieved, showcasing your research and development contributions to the field.

Qualifications

Bachelor's or Master's degree in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or a related field.
1+ years of experience in automotive embedded software development
Extensive experience in Python programming, including object-oriented programming and proficiency in libraries such as Pandas and NumPy.
Solid understanding of machine learning fundamentals, encompassing supervised and unsupervised learning techniques. Experience in data analysis and utilizing tools like scikit-learn.
Knowledge of deep learning concepts, including artificial neural networks, recurrent neural networks, and long short-term memory networks. Familiarity with deep learning frameworks like PyTorch and TensorFlow.
Basic understanding of reinforcement learning principles and experience with tools like stable-baseline and gym.
Knowledge of large language models and generative AI techniques
Experience with physics-based simulation platforms such as CARLA, Webots, or SCANeR
Strong problem-solving and analytical skills.
Ability to work independently and as part of a team.
Excellent communication and documentation skills.
Passion for AI research and development.

Other Specifications

Experience in software development for lighting systems in the automotive industry is highly desirable.
Proficiency in backend development frameworks such as Flask and React is a plus. Knowledge of other relevant backend technologies is also beneficial.
Experience with major cloud platforms like Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure is a plus
Solid understanding and experience with C and C++ programming languages is highly desirable.
Experience using MATLAB and Simulink for modeling, simulation, and analysis of systems. Familiarity with MATLAB toolboxes relevant to the specific application domain is a plus.

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