Generative Machine Learning Engineer

Innovative company ZAUBAR is bringing the metaverse to the streets with location-based augmented reality tours. Collaborating with prestigious German institutions, we're making these immersive journeys a reality and soon, we'll enable anyone to create, distribute, and monetize immersive tours. Backed by a team with strong AI, 3D UI, and journalism expertise, we're turning time travel into an interactive experience.

We're looking for an experienced Machine Learning Engineer to join our expanding team. Your role will encompass designing and implementing Deep Learning Pipelines using cutting-edge models, maintaining our Azure infrastructure, and establishing automated deployment pipelines. Staying abreast with AI trends and refining pipeline prototypes alongside the team and clients until perfected will also be key.

In a fast-paced environment where your code is quickly deployed, you'll have a high degree of ownership over product code and work closely with the team and creative and product teams to prioritize issues and opportunities. At ZAUBAR, we provide everything needed to succeed in a dynamic, employee-centric structure where you are entrusted with making time travel possible. If you're a motivated individual with a passion for machine learning, we'd love to hear from you.

Tasks

We make use of the following stack

• Cloud platform: Azure
• Deep learning framework: Pytorch
• CI/CD tools: Pytest, Github Actions, Docker
• Infrastructure as code tool: Terraform

Job Functions

• Develop and implement Deep Learning Pipelines using cutting-edge models
• Sustain the infrastructure for Deep Learning inference on Azure
• Build a CI/CD pipeline for automated deployment
• Keep up-to-date with latest developments in the AI field
• Prototype the pipelines and refine them with the team and clients until the final product

Additional tasks will include

• Managing the AI inference backend, facilitating secure frontend requests
• Designing and implementing database schema and serverless architectures

Requirements

• At least 3 years of experience with Deep Learning Pipelines
• Knowledge and experience with Azure/AWS/GCP, preferably Azure
• An approachable and friendly disposition
• The ability to see through problems to their resolution

Benefits

We provide an attractive salary and benefits package, including flexible working hours, the option to work remotely, and avenues for career advancement. If you are a highly driven individual with a fervor for machine learning, we encourage you to reach out to us!

• Please attach a portfolio of your work.