DevOps Engineer

DevOps Engineer, ML Ops

About the Opportunity: Your Impact as DevOps & ML Ops Engineer

Are you a skilled DevOps Engineer with a passion for building scalable, reliable systems, especially within the realm of Machine Learning Operations? Do you thrive in a high-impact role where you can architect foundational infrastructure? Wizard is seeking a talented and experienced engineer to join our team and play a pivotal role in shaping our technical future.

About Wizard: Revolutionizing Shopping with AI

At Wizard, we’re not just building an app; we’re reimagining the retail landscape. By harnessing the power of cutting-edge Generative AI and advanced messaging technologies, we’re creating a personalized shopping assistant for *every* consumer. Forget endless scrolling – our AI intelligently analyzes product data and ratings from across the web to find the perfect items tailored to individual needs. With a seamless, intuitive chat interface, the Wizard AI is always accessible, right where you are. This is more than just a company; it’s the future of how people discover and buy. Join us and be part of bringing this vision to life.

Your Impact & The Opportunity

This isn’t just an operational role; it’s a chance to be a foundational builder. As our DevOps Engineer focused on ML Ops, you’ll collaborate closely with our talented Application Engineering and AI/ML teams. You’ll be instrumental in designing, building, and scaling the core infrastructure that supports our platform and our complex machine learning models. Your expertise will ensure unparalleled system reliability, scalability, and robust security, directly enabling faster, more efficient development cycles. If you thrive in an environment where you have significant ownership and your work directly impacts product velocity and stability, you’ve found your place.

What You’ll Be Building & Doing

In this critical role, you will:

– Design, implement, and maintain secure, reliable, and highly scalable cloud infrastructure primarily on leading platforms (e.g., AWS, Azure, or GCP).

– Build, manage, and optimize our CI/CD pipelines for rapid, consistent, and automated deployments.

– Architect and maintain the specialized ML Ops infrastructure required for deploying, monitoring, updating, and managing machine learning models at scale efficiently and cost-effectively.

– Define, implement, and champion best practices for infrastructure management, security, incident response, and operational rigor while empowering developer productivity.

– Partner closely with Application Engineering and AI/ML teams to streamline their build, test, and deployment workflows.

– Apply rigorous software engineering principles and methodologies to the machine learning model lifecycle.

– Create and maintain clear documentation, continuously identifying opportunities to improve infrastructure and workflows.

– Automate routine operational tasks to minimize manual effort and accelerate team velocity.

– Establish and manage comprehensive monitoring and alerting systems to proactively identify and address issues.

What You Bring to the Table

We’re looking for a hands-on, proactive engineer who possesses:

– 7+ years of progressive experience in DevOps, Infrastructure Engineering, or a related field, with significant exposure to production-grade ML Ops environments.

– A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

– A proven track record of empowering engineering teams by building developer-friendly infrastructure and significantly accelerating deployment velocity.

– Hands-on expertise designing, implementing, and maintaining robust CI/CD pipelines.

– Experience setting up and managing comprehensive monitoring and alerting tools.

– Deep understanding and hands-on experience with major cloud platforms like AWS, Azure, or GCP.

– Strong problem-solving skills and the ability to troubleshoot complex distributed systems.

– Excellent communication and collaboration skills, able to work effectively across technical teams.

Salary Range

The expected salary range for this role is $185,000 – $235,000, depending on your skills, experience, and location.

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