Job Description
About Kaleris and the Role
Kaleris builds mission-critical logistics and supply chain software used by leading operators worldwide. Join our AIML team to kickstart your engineering career working on real-world AI systems that optimize yard operations, terminal throughput, routing, and decision intelligence. You’ll learn modern ML/MLOps practices and contribute to production-grade solutions in a collaborative, inclusive environment.
What You’ll Do
- Develop, test, and deploy machine learning models for core product features (classification, regression, NLP, RL).
- Build and maintain data pipelines for ingestion, cleaning, feature engineering, and labeling.
- Implement reproducible experiments and help automate training/evaluation workflows.
- Contribute to CI/CD for ML services using containers and cloud environments.
- Monitor model performance, latency, and drift; assist in troubleshooting and incident response.
- Participate in code/design reviews; write clear documentation and visualizations for stakeholders.
Minimum Qualifications
- Bachelor’s in Computer Science, Engineering, Statistics, Mathematics, or related field.
- 0–2 years of relevant experience (internships, projects, or research count).
- Proficiency in Python and core ML/data libraries: scikit-learn, pandas, numpy.
- Familiarity with building and evaluating machine learning models and metrics.
- Knowledge of Git, unit testing, and basic software engineering practices; SQL experience.
Preferred Qualifications
- Exposure to PyTorch or TensorFlow; experiment tracking (MLflow or similar).
- Experience with Docker, Kubernetes, and a major cloud (Azure/AWS/GCP).
- Interest in logistics/supply chain and reinforcement learning concepts.
Why Kaleris
- Build AI that measurably improves global operations.
- Mentorship, growth paths, and diverse project exposure across the AIML team.
- Competitive pay, comprehensive benefits, and inclusive culture.
Kaleris is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
