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Kaleris
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Enterprise Software & Network Solutions · 201 to 500 Employees · Alpharetta, US
2 open roles0 posted in 7d2 in 30d
Work-life balance 4.0Compensation & benefits 3.5Culture & values 3.8
Hiring: Engineering
What employees say
+ Work-Life Balance Really enjoyed working here
− None of the cons were found
More reviews on the company profile.
Interview experience · Softwarwe Engineer
Recruiter through online Hacker rank Technical round Non technical round Managerial round All of them was on office premises good easy to answer questions most of the question is customer oriented where how we will face
Average difficulty · Chennai · 40 reports
More interview insightsJob description
Overview
About Kaleris and the Role
Responsibilities
- About Kaleris and the Role
- Lead the architecture and delivery of scalable ML/RL systems at Kaleris. As a Senior AIML Software Engineer, you’ll set technical standards, mentor engineers, and drive initiatives from problem framing through production operations, shaping AI solutions that materially improve throughput, cost, and service reliability for global supply chains.
- Architect end-to-end ML/RL platforms: pipelines, training/evaluation environments, model serving, monitoring, and incident response.
- Establish data quality standards, observability, and governance across ML products.
- Optimize production workflows for performance, latency, scalability, and security.
- Lead technical reviews, elevate code/design quality, and ensure reproducible experimentation.
- Partner cross-functionally to translate business goals into model objectives, success metrics, and deployment strategies.
- Mentor and coach engineers and data scientists; promote best practices and continuous improvement.
Qualifications
- Bachelor’s/Master’s/PhD in Computer Science or related field; 5–8+ years building and operating ML systems in production.
- Advanced proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
- Experience building enterprise applications with Java and Spring Boot.
- Expert-level experience with scikit-learn, pandas, numpy, and machine learning model development and evaluation.
- Proven track record deploying on Azure/AWS/GCP; strong with Docker, Kubernetes, and CI/CD.
- Hands-on experience with monitoring, drift detection, alerting, and incident response for ML services.
- Simulation expertise (discrete-event or agent-based), queueing/stochastic modeling, and reinforcement learning in real-world settings.
- MLOps depth: model versioning, experiment tracking, automated retraining, governance.
- Logistics/supply chain domain experience and optimization in complex/partially observable environments.
- Experience with serverless functions and event-driven architectures for low-latency model APIs, including Knative, Azure Functions, and AWS Lambda
- Own strategic ML initiatives with direct line-of-sight to customer impact.
- Influence product direction and technical standards in a modern AI/ML organization.
- Competitive salary and benefits; inclusive culture; opportunities to grow scope and leadership.
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Job application FAQ
Last updated 26 October 2026
- How do I apply for Senior Software Engineer - AIML at Kaleris?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Kaleris may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Senior Software Engineer - AIML role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Senior Software Engineer - AIML remote or on-site in Chennai, Tamil Nadu?
- This listing is marked on_site with location Chennai, Tamil Nadu. Confirm details on the job description before applying.
- What skills matter for this Senior Software Engineer - AIML role at Kaleris?
- This is a senior Senior Software Engineer - AIML role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.