Machine Learning Ops Engineer

About Builder.ai

We’re on a mission to make app building so easy everyone can do it – regardless of their background, tech knowledge or budget. We’ve already helped thousands of entrepreneurs, small businesses and global brands, like NBC Universal and Pepsi, as well as American organizations like Bobcat and Smart Path, achieve their software goals. And we’ve only just started!
Builder.ai was voted as one of 2023’s ‘Most Innovative Companies in AI’ by Fast Company, and won Europas 2022 ‘Scaleup of the Year’. Our team has grown to over 800 people across the world and our recent announcement of $250m Series D funding (and partnership with Microsoft) means there’s never been a more exciting time to become a Builder.

Life at Builder.ai

At Builder.ai we encourage you to experiment! Each role at Builder has unlimited opportunities to learn, progress and challenge the status quo. We want you to help us become even better at supporting our customers and take AI app building to new heights.

Our global team is diverse, collaborative and exceptionally talented. We hire people for their differences but all unite with our shared belief in Builder’s HEARTT values: (Heart, Entrepreneurship, Accountability, Respect, Trust and Transparency) and a let’s-get-stuff-done attitude.

In return for your skills and commitment, we offer range of great perks, from hybrid working and a variable annual bonus, to employee stock options, generous paid leave, and trips abroad #WhatWillYouBuild

Why We Need This Role

We are looking for a Machine Learning Ops Engineer  to help us maintain and expand an ecosystem of microservices developed within the Artificial IntelligenceGroup. We leverage a range of AI techniques including large scale knowledge graphs and Generative AI (LLMs for text and images). The role includes ensuring robustness and scalability of AI-based production APIs, as well as data and model training pipelines.  As we push the boundaries of what is possible, and scale our systems to improve the services we deliver to customers and internal teams, we need individuals that can help us innovate fast, but maintain a high quality bar.

Why You Should Join

The position will be at the intersection of data science and development operations. The candidate would want to join because of the extreme variety of problems we are facing: support to data scientists in the development of AI-based production APIs; support the design, implementation, deployment, maintenance of our microservices infrastructure, data and model training pipelines. This is an engaging role and the ideal candidate should be an eager problem solver that takes pride in the production of clean, robust and scalable solutions.

Our Tech Stack

• Python
• SQL
• Cypher
• Git/Gitlab and CI/CD workflows
• Terraform
• Docker and Kubernetes (kubectl, helm, helmfile)
• AWS, Azure

• Computer Science or Software Engineering degree / BSc or higher
• Strong Python coding experience
• Experience with the SQL querying language
• Experience working with Docker both in development and deployment environments
• Experience reading/implementing CI/CD workflows
• Experience with software engineering best practices: unit testing (with mocks), code reviews, design documentation, excellent debugging, troubleshooting skills
• Excellent communication & drive to learn and experiment
• Passionate about loosely held values and ideas. We want someone who has experience but is not blinded by the path already taken.
• Makes decisions based on data and evidence.

Added bonus:

• Background in running Kubernetes
• Experience with Graph databases
• Hands-on experience in all facets of automation and systems architecture, with particular focus on Linux and open source technologies
• Experience with GitLab
• Experience working in Cloud environments, in particular Azure or AWS