Job Title
Software Engineer - Data, Workflows, AI/ML & Analytics
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About the Job
We are seeking a skilled software engineer to join our team in developing cutting-edge solutions for data analytics and machine learning. The ideal candidate will have experience with popular open-source tools such as Kubeflow, MLFlow, DVC, and Feast.
As a software engineer on this team, you will collaborate with colleagues to design, build, and maintain solutions that will be deployed on public and private clouds and local workstations.
You will work closely with a distributed team of engineers, designers, and product managers to deliver high-quality solutions.
Key Responsibilities
* Develop understanding of the entire Linux stack, from kernel, networking, and storage, to the application layer
* Design, build, and maintain solutions that will be deployed on public and private clouds and local workstations
* Master distributed systems concepts such as observability, identity, tracing
* Work with both Kubernetes and machine-oriented open-source applications
* Collaborate proactively with a distributed team of engineers, designers, and product managers
Requirements
* Professional or academic software delivery using Python
* Exceptional academic track record from both high school and university
* Undergraduate degree in a technical subject or a compelling narrative about your alternative chosen path
* Confidence to respectfully speak up, exchange feedback, and share ideas without hesitation
* Track record of going above-and-beyond expectations to achieve outstanding results
* Passion for technology evidenced by personal projects and initiatives
* Excellent interpersonal skills, curiosity, flexibility, and accountability
Nice to Have
* Proven track record of building highly automated machine learning solutions, data pipelines, or orchestrating workflows for the cloud
* Hands-on experience with machine learning libraries, or tools
* Experience with container technologies (Docker, LXD, Kubernetes, etc.)
What We Offer
* Distributed work environment with twice-yearly team sprints in person
* Personal learning and development budget of USD 2,000 per year
* Annual compensation review
* Recognition rewards
* Annual holiday leave
* Maternity and paternity leave
* Employee Assistance Programme
* Opportunity to travel to new locations to meet colleagues