What We Offer:

* Career Development

* Competitive Compensation and Benefits

* Pay Transparency

* Global Opportunities

Learn More Here:

Dematic provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.'

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

The base pay range for this role is estimated to be $ 82,000-166,000 at the time of posting. Final compensation will be determined by various factors such as work location, education, experience, knowledge, and skills.

This is What You Will do in This Role:

• Apply AI principles and technologies to solve and/or improve planning, automation, search, classification, recommendation, prediction, and optimization problems arising from the need to streamline supply chain operations, sometimes involving synthesis of components in production.

• * See solution through full development cycle from inception to proof of concept, to MVP, to final product deployment. Ensure what is delivered meets business requirements.

• Work directly with real and synthetic data from building pipelines for on-site acquisition, experimenting with datasets that are used to train models powering data-driven solutions.

• Identify and develop model-centric solutions architecture.

• Develop model-based POCs leveraging advances in GPU, Sensor Fusion, Edge and Cloud Computing technologies for performance increase of high-automation intralogistics systems.

• Design and build statistical forecasting and machine learning models.

• Support the matter experts in commercial AI and autonomy solutions delivery.

• Learn and apply new tools, technologies, and industry best practices.

What We are Looking For:

• Master's or PhD in Computer Science, Artificial Intelligence, Electrical Engineering, Operations Research, Machine Learning, Control Engineering, Industrial Engineering, or related field.

• Knowledge of standard Machine Learning models and techniques: Linear regression, logistic regression, decision trees, SVM, kNN, ensemble learning, XGBoost.

• * Knowledge of Deep Learning architectures and use cases: ANN, CNN, RNN, VAE.

• Background in Perception, Machine Vision, Robotics, or related fields.

• Experience with Python/C++, ROS, and widely used AI/ML SDKs on edge devices.

• 5+ yrs developing AI/ML solutions under Agile methodologies and CI/CD.

• 5+ yrs practicing asset control and documentation-Git, Confluence.

• Familiarity with some of the following AI and Data Science frameworks: Pandas, PyTorch, Tensorflow/Keras, MXNET, Scikit-learn, Matplotlib, Numpy, fast.ai, Tensorboard, Ignite, Neptune, etc.

• 5+ years of experience, including academic experience, in any of the above.

• 5+ yrs delivering models into production - CNNs, LSTMs, Transformers, Ensemble Classifiers, etc.

• 5 yrs usage of CUDA, PyTorch, TensorFlow-or similar.

• Experience identifying and working with applicable key open-source SDKs, frameworks, and tools.

• Ability to accommodate some domestic and international travel.

Ways to Stand Out

• PhD in Machine Learning, Mathematics, Statistics, Physics, Engineering, or equivalent experience.

• Ability to communicate with stakeholder audiences of various seniority levels and backgrounds.

• Experience with deploying ML models on the edge for real time applications, and edge lifecycle management

• Proficiency with NVIDIA's edge technologies (CUDA, Deepstream, & TensorRT SDKs.)

• Proficiency with containerization & orchestration tools like Docker, Kubernetes, Helm, Terraform

• Proficiency in Unity, Nvidia Omniverse or similar simulation engines.

• Natural inclination for and/or record of leadership and engineering best-practices- test-driven development, patterns, conventions, and delivery standards.

• Familiarity with Robotics, PLC programming, Predictive Maintenance, or Reinforcement Learning is a plus.