Key Responsibilities / what youll do:
- Model, build and test AI/ML based software that is subject to a wide variety of complex inputs.
- Use your expertise in LLMs and/or AI/ML agents to help drive our SW/tools stack while mAI/MLntAI/MLning key connection to our data frameworks (existing calibration or development guides for example)
- Work collaboratively with a team of specialists ranging from data scientists, simulation experts and calibration technical specialists to cohesively build new capability into our existing CoSimulation framework
- Use your knowledge to prototype new AI/ML solutions that fit our goals as they evolve and we future proof our technology stacks.
- Contribute to visualizations of our work and strive for physical meanings/interpretations of the AI/ML outputs.
- Challenge the status quo continuously, with a mAI/MLn AI/MLm being to further our understanding of our data.
- Master ambiguity in a way that can leverage creative insights while remAI/MLning grounded in your deliverables.
- Lead and mentor others in the team towards a common goa
Preferred candidate profile
- Positive understanding of data science, advanced statistics, signal processing and simulation frameworks
- In depth knowledge of the core programming languages (Python, JavaScript, C/C++, etc.), as well as core AI/ML toolsets and libraries (PyTorch, TensorFlow, etc.)
- Understanding and track record of developing and deploying LLM & Deep learning models, for NLP
- Knowledge of RAG, generative AI/ML techniques, and Hybrid models are a plus.
- Knowledge of Full-Stack AI/ML Deployment (e.g. scalable ML pipelines (MLOps) using Docker, Kubernetes, FastAPI, cloud services, or other modern toolsets)
- Willingness to learn and continue developing knowledge in an up-and-coming field.
- Excellent problem-solving skills with the ability to thrive in a demanding, fast-paced work environment.
- Strong interpersonal and communication skills and a willingness to collaborate cross-functionally with