About Wizard
Wizard is revolutionizing the shopping experience using the power of generative AI and rich messaging technologies to build a personalized shopping assistant for every consumer. We scour the entire internet of products and ratings across brands and retailers to find the best products for every consumer’s personalized needs. Using an effortless text-based interface, Wizard AI is always just a text away. The future of shopping is here. Shop smarter with Wizard.
The Role
We’re hiring a DevOps Engineer with ML Ops experience to lay the foundation for infrastructure, automation and security across our systems. This is a high impact role where you will work closely with our App Eng and AI teams to streamline deployments, ensure system reliability and help build a secure and scalable system.
You’ll take the lead on designing and implementing best practices for CI/CD, cloud infrastructure, monitoring, reliability and response all with a strong focus on enabling fast, frictionless development. If you thrive in an environment where you can take full ownership and have a significant impact we’d love to meet you.
Key Responsibilities:
- Design and implement secure, reliable and scalable cloud infrastructure
- Build, manage and scale CI/CD pipelines for fast and repeatable deployments
- Design, build and maintain infrastructure for deploying, monitoring and updating machine learning models in a scalable and cost effective way
- Define and enforce best practices for infrastructure, security and incident response while balancing operational rigor with developer productivity
- Work closely with app eng to streamline build/test/deploy workflows
- Apply software engineering rigor and best practices to machine learning
- Maintain accurate documentation of processes and systems and continuously improve App Eng & ML infrastructure and workflows
- Automate routine operational tasks to reduce friction and keep teams moving fast
- Set up and manage monitoring and alerting systems
You
- 7-10+ years of experience in DevOps or Infrastructure Engineering, ideally with exposure to production ML systems
- Bachelor’s or Master’s in Computer Science or a related field
- Proven track record of enabling engineering teams by building developer friendly infrastructure and accelerating deployment velocity
- Hands on experience with CI/CD tools
- Experience implementing monitoring/alerting tools
- Strong knowledge of cloud platforms such as AWS, Azure, or GCP
The expected salary for this role is $185,000 - $235,000 depending on skills and experiences.
Apply Now
Apply Now