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Summary
About the Role
About You
- Bachelor’s degree in computer science, Software Engineering, or a related field.
- 6+ years of experience in platform engineering, DevOps, or infrastructure engineering.
- Hands-on experience with Hopsworks Feature Store deployment and configuration.
- Strong knowledge of cloud platforms (AWS, Azure, or GCP) and container orchestration (Kubernetes, Docker).
- Expertise in Infrastructure-as-Code (Terraform, CloudFormation, or Ansible) for automated provisioning.
- Experience with CI/CD pipelines (GitHub Actions, Jenkins, etc.) for ML model deployment.
- Solid understanding of distributed computing, big data frameworks (Spark, Hadoop, Kafka, etc.).
- Proficiency in Python, Scala, or Bash for scripting and automation.
- Experience with feature engineering and ML model serving in production.
- Knowledge of feature drift monitoring, data validation, and model observability tools.
- Familiarity with ML frameworks (TensorFlow, PyTorch, or Scikit-learn).
- Relevant cloud or MLOps certifications (AWS Certified Machine Learning, GCP ML Engineer, etc.).
- Exposure to banking or fraud detection systems involving real-time ML processing.
Benefits
- Competitive compensation
- Comprehensive insurance options
- Matching contributions through the 401(k) plan and the share purchase plan
- Paid time off for vacation, holidays, and sick time
- Paid parental leave
- Learning opportunities and tuition assistance
- Wellness and Well-being programs
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