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.
– 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.
