Python Developer

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Responsibilities:

• Design and build scalable Python services and APIs that power our ML platform
• Develop and evolve client tooling (Python SDK and upcoming CLI) to improve how users interact with the platform
• Work on orchestration and workflow systems using tools like Celery and Argo
• Contribute to platform architecture, including ongoing work around multi-project GCP setups and system design improvements
• Collaborate with ML engineers, data scientists, and other teams to build reliable, self-service workflows for ML use cases
• Take ownership of services end-to-end: design, implementation, deployment, and operation
• Contribute to infrastructure and platform reliability, working with Kubernetes and cloud-native systems
• Participate in code reviews, design discussions, and cross-team initiatives

Who You Are:

• Strong backend engineer with deep Python experience and a track record of building production systems
• Interested in platform engineering and building internal tools that other engineers rely on
• Comfortable working across the stack, from APIs and services to cloud infrastructure when needed
• Enjoy collaborating across teams and driving work that spans multiple domains
• Curious about ML platforms and how to enable others to build and run ML workloads effectively
• Experience with architectural decisions or technical leadership is a plus, but not a requirement

Must-Have Skills:

• Strong experience building backend services and APIs in Python
• Experience designing and operating distributed systems in production
• Familiarity with containerized environments and Kubernetes
• Experience working with cloud platforms (GCP is a plus, not required)
• Experience with asynchronous or workflow-based systems (e.g. Celery or Argo Events)
• Solid understanding of software engineering best practices (testing, CI/CD, observability)
• Fluent in English, with strong written and verbal communication skills

Nice-to-Have Skills:

• Experience with infrastructure orchestration tools like Crossplane or Terraform
• Exposure to ML platforms or tooling (e.g. MLFlow, Vertex AI, Dataproc)
• Experience working in environments with multiple cloud projects or multi-tenant systems
• Interest in improving developer experience and self-service platforms