About the role
Logibee's AI Route Intelligence and control-tower capabilities depend on models that understand demand, constraints, and real-world variability. As an AI Engineer, you will design and productionize ML solutions that help planners and dispatchers make faster, better decisions.
You will partner with platform engineers and product leaders to move models from experiment to reliable services — with clear evaluation, monitoring, and iteration loops.
Who can apply
- Minimum 3 years of professional experience as a Python developer focused on AI/ML.
- Strong problem-solving skills and solid grounding in algorithms, data structures, and software architecture.
- Fluency in Python data and ML stacks: Pandas, NumPy, SciPy, PySpark, PyTorch, Matplotlib.
- Experience with regression, NLP, CNN/DNN, decision trees, deep learning, and model evaluation.
- Ability to design RESTful APIs that expose model outputs to platform services.
- Working knowledge of MongoDB, Postgres, or similar data stores for feature pipelines.
- Hands-on AWS experience; SageMaker and AWS ML certifications are a plus.
- Comfort working with remote, cross-functional engineering teams.
What you will do
- Understand logistics workflows and translate operational problems into ML problem statements.
- Build, validate, and deploy models for routing, forecasting, anomaly detection, or decision support.
- Create reusable training pipelines, feature stores, and inference services integrated with Logibee platform APIs.
- Monitor model performance in production and iterate with product feedback from enterprise customers.
- Document approaches, trade-offs, and evaluation metrics so teams can trust and extend your work.
Why Logibee
Logistics is one of the richest applied-AI domains — noisy data, hard constraints, and decisions that affect cost, SLA, and customer experience every hour. Your models will not live in a slide deck; they will influence live operations.
Join a team that treats intelligence as a product capability, not a side project.