[About the job]
Our team is looking for experienced engineers to work on exciting technical problems for marketing AI. On the 8ndpoint team, you’ll have the opportunity to own and drive projects that help us scale the platform. As a Senior Backend Engineer, you’ll manage the infrastructure that powers our internal services and external facing applications, using both DevOps and application engineering. You’ll have wide latitude to direct engineering to adopt new technologies and solutions.
MoBagel has an extraordinarily open and relaxed work culture. There’s immense freedom to work on what you think is most important, and generous support for personal development. We’re a small and rapidly growing team with great work-life balance, generous remote work policy, open and supportive teammates, and free food. Come meet the team!
Since this role is highly cross-functional, there are ample opportunities (and support) for diving into DevOps, MLOps, data engineering, and machine learning modeling projects.
1. Develop existing services and infrastructure, and decide how to scale and/or migrate to new technologies.
2. Build and maintain scalable applications in close collaboration with product and data science.
3. Design and build CI/CD pipelines and integration testing infrastructure.
4. Evangelize and encourage best software development practices through documentation, code reviews, and sharing.
5. Write technical documentation, conduct thorough code reviews, and share technical knowledge and decisions with the team.
1. 3+ years of professional software development experience.
2. Experience with CI/CD pipelines and integration testing.
3. Experience with backend application development: RESTful API, relational databases, networking.
4. Experience with Kubernetes and containerization (e.g., Docker).
[Nice to Have]
1. Experience with cloud services (e.g., GCP, AWS, Azure).
2. Experience with event streaming architectures and protocol buffers or other serialization protocols.
3. Experience on a data or machine learning team in a production environment.
4. Familiarity with distributed data systems fundamentals.
5. Eager to research, learn, and implement new technologies on your own.
We prioritize candidates that can quickly learn new technologies over domain knowledge, but the following is a snapshot of what our day-to-day looks like:
1. Development: Python, Java, Scala
2. Machine Learning: Python (Pandas, sklearn, xgboost, etc.)
3. Orchestration: Airflow, Kubernetes, Docker
4. GCP: BigQuery, GKE, Artifact Registry, Cloud SQL, Pub/Sub
5. Frontend: React, TypeScript
6. DevOps: ArgoCD, Rancher/Longhorn
7. VCS & CI/CD: Gitlab