AI Scientist

Homebased, MI, United States

KION Group

Wir sind ein führender Anbieter für Gabelstapler und Lagertechnik sowie Automatisierungstechnologien und Softwarelösungen für die Optimierung von Lieferketten.

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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 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 Machine Learning, Computer Vision, and Operations Research. The candidate should not only have a solid grasp of theoretical approaches 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 offer:
  • 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.

Tasks and Qualifications:

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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Tags: Anaconda ANN Architecture AWS Azure Computer Science Computer Vision Deep Learning Docker Engineering fastai GCP Git Industrial Java Jupyter Keras Kubernetes Machine Learning Mathematics Matlab Matplotlib ML models Monte Carlo MVP MXNet NumPy OOP OpenAI Pandas PhD Python PyTorch R Reinforcement Learning Research RNN Scikit-learn SQL Statistics TensorFlow Weights & Biases XGBoost

Perks/benefits: Career development Competitive pay

Region: North America
Country: United States

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