About the Role
Machine Learning Engineer Senior
Requirements
- 4–6 years of experience in ML engineering
, with strong expertise in
MLOps and system architecture
. - Proficiency in
Python
and ML frameworks such as
TensorFlow, PyTorch, and Scikit-learn
. - Hands-on experience with
MLOps tools
(MLflow, Kubeflow, SageMaker, Airflow). - Strong knowledge of
cloud platforms
(AWS, Azure, GCP) and
containerization technologies
(Docker, Kubernetes). - Experience with
model monitoring, logging, and performance optimization
. - Solid understanding of
data pipelines, APIs, and distributed systems
. - Preferred certifications:
AWS Machine Learning Specialty, Google Professional ML Engineer, or equivalent. - Advanced English proficiency
, able to document and present technical solutions to diverse stakeholders.
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