We are seeking a backend engineer with a strong foundation in building scalable, high-performance systems and a deep understanding of cloud infrastructure, distributed systems, and data pipelines. This role focuses on designing and optimizing backend services that support our machine learning (ML) operations and real-time personalization capabilities.
We foster a professional environment where experienced engineers collaborate to drive technical excellence, continuously improving our backend architecture and infrastructure. As a Backend Engineer, you will play a key role in building and maintaining the backend services that power our ML infrastructure, ensuring efficiency, scalability, and reliability.
Role & Responsibilities:
- Design, develop, and optimize backend services that support ML pipelines, APIs, and real-time decision-making systems.
- Architect and implement scalable and reliable data processing workflows, integrating ML models into production environments.
- Build and maintain infrastructure for efficient model deployment, monitoring, and versioning.
- Ensure high availability, performance, and security of backend services.
- Lead initiatives to improve system architecture, reduce technical debt, and enhance development processes.
- Stay up to date with the latest advancements in backend technologies, cloud computing, and distributed systems.
Requirements: - 4+ years of experience in backend engineering, designing and developing distributed systems.
- Strong proficiency in Python, Java, or Go for backend development.
- Deep experience with cloud platforms (AWS, GCP, or Azure), including compute, storage, and networking services.
- Experience with containerization and orchestration (Docker, Kubernetes).
- Proficiency in designing and managing scalable databases (SQL & NoSQL: MySQL, PostgreSQL, Redis, Cassandra, etc.).
- Hands-on experience with CI/CD pipelines, infrastructure as code (Terraform, CloudFormation), and automated deployments.
-Familiarity with high-performance APIs and microservices architecture.
- Experience working with ML operations (MLOps) and data pipelines is a plus but not required.
This position is open to all candidates.