AI Scientist

KION Group•Atlanta, GA

1d•Hybrid

About The Position

We are seeking an AI Scientist to join our Data Platform and AI team within Software Product Development. You will help design, build, and deploy intelligent solutions for intralogistics planning and operations, partnering with business stakeholders, product managers, application engineers, and subject-matter experts to turn complex operational challenges into scalable, data-driven products. This role is well-suited to early-career professionals who are passionate about applied AI, machine learning, and optimization and who want exposure to the full solution lifecycle—from ideation and proof of concept through deployment and continuous improvement.

Requirements

Bachelor's degree in Engineering or related + 3 years of relevant experience or Master's degree in Engineering or related + 2 years of relevant experience.
4+ years of experience with ML frameworks and toolchains (e.g., PyTorch, TensorFlow, scikit-learn, or equivalents)
4+ years of working knowledge of software engineering fundamentals (e.g., version control, testing, and code quality practices)
Strong foundation in statistics and machine learning algorithms
Proficiency in at least one programming language commonly used in AI/ML (e.g., Python, C++, Java)
Ability to communicate technical concepts clearly to both technical and non-technical audiences
Ability to travel up to 15% of the time
Applicants must be authorized to work in the U.S. without the need for current or future sponsorship.

Nice To Haves

Experience working with cloud platforms (Azure or GCP)
Familiarity with optimization and/or operations research concepts
Experience with reinforcement learning and/or large language models (LLMs), including LLM-based applications
Interest in applied AI within supply chain, logistics, or industrial automation

Responsibilities

Translate business problems in intralogistics planning and operations into clear, quantitative problem statements (analytics, machine learning, optimization, and AI).
Contribute to the solution development lifecycle and progressively take ownership across phases, including: Partnering with business stakeholders and product managers on problem framing and ideation, Building proof-of-concept (PoC) prototypes with peer AI scientists, Collaborating with engineering teams on MVP deployment, productization, and iterative enhancements.
Work with real-world and synthetic datasets to develop, train, and evaluate models.
Design and develop forecasting, machine learning, and optimization models for intralogistics use cases.
Apply AI techniques to problems such as: Planning, scheduling, and resource allocation, Automation, autonomy, and control strategies, Prediction and optimization of supply chain and intralogistics systems.
Design and build simulation tools to support model training, validation, and testing of intralogistics processes.
Develop model-centric solution architectures that integrate ML models, data pipelines, and inference services.
Write clean, maintainable code following software engineering best practices and internal standards.
Support subject-matter experts and engineering teams in delivering commercial AI and autonomy solutions.