minds.ai is a company focused on transforming semiconductor manufacturing with AI. They offer deep learning solutions to optimize semiconductor operations and planning, enhancing existing workflows and improving operational KPIs across all fabs. Their AI engine, DeepSim, combines open-source and proprietary AI tools into a cloud-based platform. minds.ai Maestro uses DeepSim to optimize processes for leaders in large-scale semiconductor manufacturing.

Responsibilities:

1. The data scientist in a team has a varied role, which can include working directly with customers to support the deployment of products or internally to strengthen the products themselves.
2. Your work will vary from initial data exploration to modeling and problem formation, and then finally to the Reinforcement Learning training itself.
3. Subspecialties within this broad scope are encouraged.
4. You will work collaboratively with backend, product, and AI teams.

Experience Requirements:

1. Experience with some form of Deep Learning, for example, image recognition or NLP, and a solid understanding of the foundations.
2. Experience with programming in Python.
3. Good knowledge of statistics, data analysis, and modeling methods.
4. Good working knowledge of Docker, Kubernetes, Terraform, and other cloud-native technologies.
5. Experienced with working with public cloud providers (e.g., Azure, GCP, or AWS).
6. Excellent debugging skills of distributed systems software and willingness/ability to go under the hood when required.
7. Strong programming background with extensive experience in Python.
8. Familiarity with software engineering best practices.

Other Requirements:

1. Good written and verbal communication.
2. Demonstrated ability to work with minimal to no supervision.
3. Ability to work remotely with cross-cultural teams.
4. Self-motivation to learn new concepts and an excellent record of execution.
5. A sense of urgency, result-orientedness, and excellent ability to prioritize.

Minimum Qualifications:

1. BS, MS, PhD in a quantitative field, such as Physics, Mathematics, Statistics, Engineering, or equivalent practical experience.
2. BS, MS in Computer Science or a related field, or equivalent practical experience.