Senior Software Developer - ML, Core Team

At our company, were reinventing DevOps and MLOps to help the worlds greatest companies innovate -- and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if youre willing to do more, your career can take off. And since software plays a central role in everyones lives, youll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, trust our company to manage, accelerate, and secure their software delivery from code to production - a concept we call liquid software. Wouldn't it be amazing if you could join us in our journey?
Are you a platform engineer who thrives on designing and building scalable, high-quality services and infrastructure?Do you want to work on cutting-edge services while shaping the backbone of an ML platform? If so, wed love to have you join our company's ML our MLOps group.
As a Senior Platform Engineer, you will play a critical role in architecting and developing cloud based core services and infrastructure with a strong emphasis on clean code, performance, observability, monitoring, and security. This role also includes developing core Go/Java libraries, cross-cutting services like authentication and authorization, Kubernetes deployments, billing etc.You will collaborate closely with engineering teams, DevOps, architects, and product managers to ensure a scalable, stable, and high-performing system.
As a Platform Engineer at our company's ML you will...
Write clean, maintainable, and efficient code following best practices.
Design and develop robust backend services with scalability, performance, and security in mind.
Conduct high-quality code reviews and architecture discussions, ensuring best practices are followed.
Take full ownership of projects - from ideation and design to production deployment and maintenance.
Collaborate with cross-functional teams to define, design, and ship new features.
Stay current with industry trends, technologies, and best practices in software development and cybersecurity.
Be involved in multiple aspects of an ML platform - from data sources to inference pipelines.