Machine Learning Engineer - ML Ops
Builder
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 Engineer to help us maintain and expand an ecosystem of microservices developed within the Intelligent Systems Group. This includes ensuring robustness and scalability of AI-based APIs, as well as data and model training pipelines.
What we are looking for
Ability to work in a team and great communication skills. Confident, but realistic, in their own skills and open to learning new approaches and solutions. Strong software engineering experience with Python (no data science experience required). Experience working on production-level microservices (Docker/Kubernetes) and cloud infrastructure. Experience working with Databases, Postgres, Redshift, Neo4j would be a plus.
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 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