Design and maintain the infrastructure for machine learning systems, automate pipelines, implement monitoring, and ensure scalability and security.
About Us
Wizard is the top-performing AI Shopping Agent, delivering the best products from across the web with unmatched accuracy, quality, and trust.
The Role
We are seeking a Senior MLOps Engineer to design and maintain the infrastructure that powers our production machine learning systems. You will work at the intersection of ML and infrastructure, building the pipelines, tooling and monitoring that enables fast, reliable model deployment at scale.
Key Responsibilities:
- Design, build and maintain infrastructure for deploying, monitoring and updating machine learning models at scale
- Automate end to end model pipelines from ingestion and preprocessing to training, validation and deployment
- Implement monitoring for model performance, accuracy, drift and latency
- Ensure ML systems are secure, cost efficient and scalable in production
- Document and continuously improve ML infrastructure, workflows and tooling
- Partner with ML engineers, scientists and product to move models seamlessly from research to production
- Apply software engineering best practices (testing, CI/CD, version control) to ML systems
You
- 5+ years of experience in ML Ops including ownership of production ML systems
- Bachelor’s or Master’s in Computer Science or a related field
- Strong expertise in Python and ML/DS libraries (e.g. TensorFlow, PyTorch)
- Experience with machine learning lifecycle management tools
- Hands on experience deploying and monitoring deep learning models
- Strong knowledge of cloud platforms such as AWS, Azure, or GCP
The expected salary for this role is $185,000 - $210,000 depending on skills and experiences.
Top Skills
AWS
Azure
GCP
Python
PyTorch
TensorFlow
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