What we offer:

Our Warehouse Execution Software leverages advances in classical and modern optimization techniques to bring intelligent execution to the world of intralogistics and warehouse automation. We synchronize the discrete and low-level logistics related processes to create a real-time decision engine that drives labor and equipment at the highest efficiency. Our software provides customers the operational agility they need to efficiently handle the demands of an Omni-channel environment.  We are looking for a highly motivated individual who can develop cutting edge MLOps and DevOps frameworks to deploy AI models.  The candidate should have a solid grasp of state-of-the-art cloud technologies, best in class deployment architectures/frameworks and production grade software.  Finally, the role requires strong team and interdisciplinary collaboration to see products through the development cycle from beginning to end. Our Warehouse Execution Software leverages advances in classical and modern optimization techniques to bring intelligent execution to the world of intralogistics and warehouse automation. We synchronize the discrete and low-level logistics related processes to create a real-time decision engine that drives labor and equipment at the highest efficiency. Our software provides customers the operational agility they need to efficiently handle the demands of an Omni-channel environment.  We are looking for a highly motivated individual who can develop cutting edge MLOps and DevOps frameworks to deploy AI models.  The candidate should have a solid grasp of state-of-the-art cloud technologies, best in class deployment architectures/frameworks and production grade software.  Finally, the role requires strong team and interdisciplinary collaboration to see products through the development cycle from beginning to end. 

Tasks and Qualifications:

• BS/MS in Computer Science, Software Engineering, or equivalent field
• Experience with Cloud Platforms, especially GCP, and related skills: Docker, Kubernetes, edge computing.
• Familiarity with task orchestration tools, such as MLflow, Kubeflow, Airflow, Vertex AI, Azure ML, etc.
• Fluency in at least one general purpose programming language, Python preferred. 
• Strong DevOps skills: Linux/Unix environment, testing, troubleshooting, automation, Git, dependency management, and build tools (GCP Cloud Build, Jenkins, Bazel, Gitlab CI/CD, Github Actions, etc.).
• Data engineering skills a plus, such as Beam, Spark, Pandas, SQL, Kafka, GCP Dataflow,  etc.
• 5+ years of experience, including academic experience, in any of the above.
• 3+ years of managing a DevOps/MLOps team.