Searching for an AI Research Scientist to join our team, focusing on Machine Learning for Physical Systems. This is a crucial role for our product and research initiatives.
What You’ll Do:
- Research and develop innovative ML models and algorithms to tackle complex problems in physical systems, with a focus on areas like digital twins, optimization, predictive maintenance, and control systems.
- Collaborate with engineers and domain experts to integrate research prototypes into production systems, ensuring scalability, reliability, and real-world applicability.
- Contribute to the scientific community through publications, presentations, and active participation in relevant conferences and workshops.
- Mentor junior researchers and foster a culture of scientific excellence and continuous learning within the team.
- Stay up-to-date with the latest advancements in ML, AI, and related fields, and proactively identify opportunities for their application to products and services.
Who You Are:
- Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative field.
- Proven track record of research excellence in machine learning, particularly in areas relevant to physical systems (e.g., reinforcement learning, optimal control, Gaussian processes, Bayesian inference, deep learning for time series, surrogate modeling).
- Strong programming skills in Python, coupled with experience in ML frameworks such as PyTorch or TensorFlow.
- Excellent problem-solving abilities, with a capacity to translate complex research challenges into actionable solutions.
- Exceptional communication and collaboration skills, with a demonstrated ability to work effectively in interdisciplinary teams.
Bonus Points:
- Experience with industrial control systems, process optimization, or predictive analytics in manufacturing, energy, or other relevant industries.
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Experience with real-time data processing and distributed systems.
We are committed to building a diverse and inclusive team. We encourage applications from candidates of all backgrounds, experiences, and perspectives. If you meet most of the qualifications and are excited about this opportunity, we encourage you to apply!
