You will transform experimental models into efficient, reliable, and maintainable products by bridging the gap between innovation and execution
Job Summary
You will transform experimental models into efficient, reliable, and maintainable products by bridging the gap between innovation and execution.
The role involves building and optimizing end-to-end ML pipelines to ensure scalability, efficiency, and reproducibility across enterprise systems.
Kyndryl offers a flexible, supportive environment prioritizing well-being with access to cutting-edge learning opportunities and personalized development goals.
Matching Summary
You will transform experimental models into efficient, reliable, and maintainable products by bridging the gap between innovation and execution.
Skills & Requirements
Must-have
3-5 years production AI/ML experience
Python proficiency with TensorFlow PyTorch
MLOps frameworks MLflow Kubeflow Airflow
Docker Kubernetes containerization orchestration
Cloud AI platforms Azure ML Vertex SageMaker
Nice-to-have
Experience with LLMs RAG architectures multi-agent systems
Knowledge of streaming data real-time serving
Familiarity with observability tools Prometheus Grafana
Passion for automation optimization reproducibility
Strong collaborative mindset and analytical thinking
Key Requirements
Bachelor's or Master's degree in Computer Engineering Data Science or related field
3-5 years experience developing and deploying AI/ML models in production
Postgraduate studies in Artificial Intelligence or Software Engineering highly valued