Highlights
High-impact ML work, global collaborative team, career progression opportunities.
Description
Job Summary
pJoin Kaleris as an AIML Software Engineer, where you will design, build, and maintain advanced machine learning systems. Collaborate with data scientists to deliver scalable solutions for decision-making in logistics and supply chain.
Responsibilities
- Owning end-to-end ML workflows: from data ingestion to deployment
- Implementing robust model serving and APIs for reliability, performance, and security
- Developing simulators/training environments for safe evaluation of models
- Automating CI/CD pipelines using containers and cloud-native tools
- Monitoring model health, detecting drift, running A/B tests, and supporting automated retraining
Required Skills
- Python programming with machine learning libraries
- Data wrangling and SQL proficiency
- Experience with PyTorch or TensorFlow
- CI/CD pipelines deployment with Docker/Kubernetes
- Strong testing and debugging skills
Required Skills Explained
- Strong Python skills with hands-on experience using scikit-learn, pandas, numpy, and machine learning algorithms.
- Experience with PyTorch or TensorFlow for model implementation.
- Proficiency in SQL and large-scale data wrangling techniques.
- Knowledge of Git and proficiency in unit/integration testing and CI/CD pipelines.
- Experience deploying applications to Azure, AWS, or GCP using Docker and Kubernetes.
- Reinforcement learning exposure or experience with simulation tools like discrete-event or agent-based systems.
- Hands-on experience building enterprise applications with Java and Spring Boot.
- Knowledge of model governance, monitoring, and automated retraining processes.
- Domain knowledge in logistics or supply chain operations is a plus.
- Experience with serverless functions for model serving and event-driven data processing, such as Knative, Azure Functions, and AWS Lambda (Amazon Lambda).
Who is this for
pThis role suits individuals with a passion for machine learning and its application in logistics. Ideal candidates have hands-on experience with Python, ML frameworks, and cloud services.
Why This Job is a Good Opportunity
ulliWork on high-impact ML projects that drive decision-making in logistics and supply chain.liJoin a collaborative global team with clear career progression opportunities.liCompetitive compensation package along with comprehensive benefits.liA culture that values inclusion, craftsmanship, and employee growth.
Interview Preparation Tips
- Review the minimum and preferred qualifications to tailor your resume and cover letter effectively.
- Prepare examples of projects or experiences related to ML workflows, model serving, and CI/CD pipelines.
- Be ready to discuss your experience with Python libraries like scikit-learn, pandas, numpy, PyTorch, and TensorFlow.
- Demonstrate your proficiency in SQL and data wrangling techniques by providing examples from past projects.
- Show your understanding of Git workflows and CI/CD practices through relevant project experiences.
- Explain how you have deployed applications to cloud environments like Azure, AWS, or GCP using Docker and Kubernetes.
- Come prepared with discussions on reinforcement learning exposure or simulation experience if applicable.
- Be ready to explain your approach to model governance, monitoring, and automated retraining.
- Highlight any domain knowledge in logistics or supply chain operations that you possess.
- Discuss your experience with serverless functions for model serving and event-driven data processing.
Career Growth in This Role
pThe AIML Software Engineer role at Kaleris offers significant opportunities for growth. With a focus on end-to-end ML workflows, professionals can advance their technical skills by mastering new tools and methodologies. The team environment provides ample chances to collaborate with data scientists and product teams, fostering a rich learning ecosystem. As the company grows, so do career progression paths, offering leadership roles that allow you to influence broader strategic decisions in decision intelligence for supply chains.
Explore More Opportunities
Skills
Frequently Asked Questions
What is the ideal experience level?We are looking for 2-4 years of ML/software engineering experience.
Do I need domain knowledge in logistics/supply chain?Domain knowledge in logistics/supply chain operations is preferred but not mandatory.
What cloud platforms are you using?We primarily use Azure, AWS, and GCP for deploying our ML systems.
