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Wizard AI

Dev Ops / ML Ops Engineer

Sorry, this job was removed at 04:02 p.m. (EST) on Tuesday, Sep 09, 2025
Remote
Hiring Remotely in USA
Remote
Hiring Remotely in USA

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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
  • Bonus: Python or Typescript experience
  • Bonus: Experience with LLMs

The expected salary for this role is $185,000 - $235,000 depending on skills and experiences.

HQ

Wizard AI New York, New York, USA Office

New York, New York, United States, 10013

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

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