Kaleris – Associate AIML Software Engineer

Job Description

Kaleris is hiring for the position of Associate AIML Software Engineer, offering an exciting opportunity for aspiring AI and Machine Learning professionals to work on real-world logistics and supply chain optimization solutions. This role is ideal for fresh graduates and early-career engineers who are passionate about artificial intelligence, machine learning, data engineering, and cloud technologies. As part of Kaleris’ AIML team, candidates will contribute to the development of intelligent systems that improve yard operations, terminal throughput, routing efficiency, and operational decision-making for global logistics providers. The role provides hands-on experience with production-grade AI applications while working in a collaborative, innovation-driven environment focused on solving complex business challenges using advanced technologies.

The Associate AIML Software Engineer role involves designing, developing, testing, and deploying machine learning models for various enterprise applications including classification systems, regression models, natural language processing solutions, and reinforcement learning-based applications. Candidates will work closely with experienced AI engineers, data scientists, and software developers to build scalable ML pipelines, automate workflows, and improve model performance across production systems. The position also offers exposure to modern MLOps practices, cloud infrastructure, CI/CD automation, and containerized deployment environments using tools such as Docker and Kubernetes. Engineers in this role will actively participate in code reviews, experimentation workflows, and performance optimization activities to ensure reliable and efficient AI solutions.

This opportunity at Kaleris is an excellent career starting point for candidates looking to establish themselves in the fields of Artificial Intelligence, Data Science, Machine Learning Engineering, and MLOps. Employees will gain practical industry exposure while working on impactful AI-driven solutions that improve global logistics and supply chain operations. Kaleris promotes a supportive and inclusive work culture where innovation, learning, and collaboration are highly valued. With mentorship programs, diverse project exposure, and access to enterprise-level AI technologies, this role provides strong long-term career growth opportunities for professionals interested in advanced analytics, cloud-based machine learning systems, and intelligent automation solutions.

Roles & Responsibilities

• Develop, test, and deploy machine learning models for enterprise applications involving classification, regression, natural language processing, and reinforcement learning use cases.
• Build and maintain scalable data pipelines for data ingestion, preprocessing, feature engineering, labeling, and transformation to support machine learning workflows.
• Assist in designing reproducible machine learning experiments and automate model training, evaluation, and validation processes using modern MLOps practices.
• Collaborate with cross-functional engineering teams to integrate AI and machine learning capabilities into production-grade logistics and supply chain software solutions.
• Contribute to CI/CD pipeline development for machine learning services using containerization technologies such as Docker and orchestration tools like Kubernetes.
• Monitor machine learning model performance, latency, drift, and prediction accuracy while supporting troubleshooting and incident resolution activities.
• Participate in code reviews, technical discussions, and software design sessions to improve application quality, maintainability, and engineering standards.
• Create clear technical documentation, reports, and data visualizations to communicate insights, model behavior, and system performance to stakeholders.
• Work with cloud-based environments such as AWS, Azure, or Google Cloud Platform to support scalable AI deployment and infrastructure management.
• Implement unit testing and software engineering best practices to ensure reliability, scalability, and maintainability of AI-powered applications.
• Support experimentation with advanced AI concepts including reinforcement learning, predictive analytics, and intelligent optimization systems.
• Continuously learn emerging machine learning frameworks, cloud technologies, and AI engineering methodologies to improve technical expertise and innovation capabilities.

Requirements & Eligibility

• Candidates must possess a Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, Artificial Intelligence, or a related technical field.
• Applicants with 0–2 years of relevant experience, including internships, academic projects, research work, or practical machine learning exposure, are eligible to apply.
• Strong proficiency in Python programming is required for developing machine learning models, automation scripts, and AI-driven software applications.
• Hands-on knowledge of machine learning and data science libraries such as scikit-learn, pandas, and NumPy is essential for working on AI workflows.
• Candidates should have a good understanding of machine learning concepts, model evaluation metrics, data preprocessing techniques, and predictive analytics fundamentals.
• Familiarity with Git version control systems, unit testing methodologies, and basic software engineering practices is important for collaborative development environments.
• Working knowledge of SQL and database concepts is required for handling structured datasets, querying data, and supporting analytics workflows.
• Exposure to machine learning frameworks such as PyTorch or TensorFlow will provide an additional advantage during the hiring process.
• Understanding of cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform along with containerization tools like Docker and Kubernetes is preferred.
• Candidates interested in logistics technology, supply chain optimization, reinforcement learning, and enterprise AI systems will be highly suited for this role.

Expected Salary

The expected salary for the Kaleris Associate AIML Software Engineer role in Chennai generally ranges between ₹6 LPA to ₹10 LPA depending on educational background, technical skills, internship experience, AI project exposure, and expertise in machine learning frameworks and cloud technologies. Candidates with strong Python programming skills, MLOps exposure, and hands-on AI development experience may receive higher compensation packages.

In addition to competitive salaries, Kaleris offers mentorship opportunities, exposure to production-grade AI systems, learning-focused work culture, and long-term career growth opportunities in Artificial Intelligence, Data Science, Machine Learning Engineering, and cloud-based enterprise software development.

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