AI Optimization Engineer

ID
2021-16109
Job Locations
US-Any Location
Category
Engineering
Job Type
Regular/Permanent
Job Time
Full-Time
Experience Level
Entry Level
Education Level
Bachelors Degree
Travel %
5
Shift Schedule
Standard
Posting Date
1 month ago(4/6/2021 3:22 PM)

Company Overview

Dematic is a global leader providing a comprehensive range of intelligent intralogistics and materials handling solutions. With a global knowledge network of more than 6,000 highly skilled logistics professionals, Dematic is able to provide its customers a unique perspective in world class materials handling solution design.  Our mission is to improve efficiency and logistics processes with integrated systems, services and products - worldwide.  Our commitment to product and solution R&D combined with manufacturing plants in the US, Europe, China and Australia ensures Dematic has the range and capability to provide reliable, flexible, cost effective solutions globally.  Our tremendous track record of success has led to the development and implementation of more than 4,500 world class integrated systems for a customer base including some of the world's biggest companies. Our employees at Dematic work in an international network of experts where the willingness to cooperate and exchange knowledge is crucial to commercial success.   The requirements for working successfully at Dematic are characterized by a high degree of flexibility in taking specific customer requests into account, and the ability to realize them efficiently in a network of experts.

The Role

Our Warehouse Execution Software leverages advances in classical and modern optimization techniques to bring intelligent execution to the world of intralogistics and warehouse automation. We synchronize the discrete and low-level logistics related processes to create a real-time decision engine that drives labor and equipment at the highest efficiency. Our software provides customers the operational agility they need to efficiently handle the demands of an Omni-channel environment.  We are looking for a highly motivated individual who can develop cutting edge algorithms using domain knowledge from Artificial Intelligence, Machine Learning, and Operations Research.  The candidate should have a solid grasp of theoretical approaches to discrete optimization but also a practical mindset regarding the tradeoffs between solution complexity versus optimality, emerging versus proven techniques, and coding from scratch versus utilizing existing frameworks.  Many of the problems we encounter are novel and have never been solved before, so creative, out-of-the-box thinking and a fondness for experimentation are a must.  We also want someone who stays current with recent trends in AI/ML so our approaches remain the most robust and competitive in the industry.  Finally, the role requires strong team and interdisciplinary collaboration to see products through the development cycle from beginning to end. 

 

What We Are Looking For

Core Job Responsibilities:

  • Frame and solve variety of intralogistics and planning problems with advanced analytics and AI techniques.
  • 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 to train models and build data-driven solutions.
  • Design and build simulation tools of intralogistics processes to train and test models.
  • Design and build statistical forecasting and machine learning models.
  • Learn and apply new tools, technologies, and industry best practices.

 

Key Qualifications

  • Master’s or PhD in Computer Science, Artificial Intelligence, Operations Research, Applied Mathematics, Control Engineering, Industrial Engineering, or equivalent field.
  • Fluency in at least one general purpose programming language. Python or Java preferred.  Statistical or database languages also a plus: R, MATLAB, SQL, etc.
  • Knowledge of Reinforcement Learning / Approximate Dynamic Programming: MDP, Monte Carlo, MCTS, TD, Dyna-Q, online vs. offline learning, exploration strategies (epsilon-greedy, optimistic initial values, UCB1, etc.), DQN, DDQN, Dueling DQN, DDPG, REINFORCE, A2C, A3C, PPO, TRPO, SAC, MARL.
  • Knowledge of Control Theory: Optimal control, MPC, LGQ, Adaptive Control
  • 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.
  • Familiarity with some of the following AI and Data Science frameworks: Pandas, PyTorch, Tensorflow/Keras, MXNET, Scikit-learn, Matplotlib, Numpy, fast.ai, Tensorboard, Ignite, Weights & Biases, etc.
  • 2+ years of experience, including academic experience, in any of the above.

Ways to Stand Out

  • Experience with RL Frameworks: OpenAI Gym, Dopamine, RLLib, OpenAI Baselines, Stable Baselines, Garage, Coach, etc.
  • Experience with simulation and modeling tools: AnyLogic, Arena, Panda3D, Simio, SimPy, etc.
  • Familiarity with any software IDE: PyCharm, IntelliJ, Visual Studio, Jupyter Notebook, etc.
  • Familiarity with Cloud Computing: GCP, Azure, AWS, Docker, Kubernetes, edge computing
  • Other software engineering skills: Git, Anaconda, OOP, test-driven design, common design patterns, dependency management, and build tools.

Dematic is committed to supporting your continued professional growth. We offer training specifically aimed at your personal development and tailored to your individual job requirements.  In addition to a great work environment, we offer a competitive compensation & benefits package.

 

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