Backend Engineer with ML focus

Our company descriptionMission is a platform for hiring, vetting and managing software development talents. It enables our clients to connect with the world’s best talent to build mission-critical software products.Our mission is to make advanced AI accessible to every organization—not just teams with large data science departments or deep technical resources.About the CompanyThis enterprise software company provides an AI platform designed to automate complex operations such as demand forecasting and supply chain optimization. The platform bridges the gap between experimental pilots and production-ready workflows, enabling organizations in global industries to deploy scalable AI solutions. By focusing on governed intelligence and data integration, the company helps businesses achieve operational efficiency through an interface for building and managing production-grade AI applications at scaleAbout the RoleAs a software engineer, you will design and own production systems end-to-end, focusing on the infrastructure required to operationalize machine learning models. You will be responsible for building the scalable APIs, microservices, and data pipelines that support reliable AI applications. Rather than focusing on model training, your impact lies in shipping the robust systems that surround these models, ensuring high performance, fault tolerance, and observability at scale. You will act as the primary bridge between core backend engineering and machine learning deploymentWhat You'll DoDesign and maintain scalable APIs and microservices to support high-throughput production environments.Build robust data pipelines for model ingestion and processing using SQL and NoSQL databasesDeploy machine learning models via specialized inference frameworks and serving patterns like batching and async infereImplement observability across the stack, including comprehensive logging, metrics, and alerting systems.Architect distributed systems focusing on low latency, fault tolerance, and message queuing.Triage and debug machine learning models in production to ensure consistent performance and reliability.Manage embedding pipelines and integrate vector search capabilities to enhance application intelligeceWhat You BringExtensive experience building and maintaining production-grade backend systems in languages such as Python, Go, or Java.Strong understanding of system design principles, including distributed systems and data consistency.Technical proficiency with SQL and NoSQL databases, caching layers, and message brokers like Kafka or Redis.Proven experience shipping to production with built-in observability and monitoring.Practical knowledge of machine learning libraries such as PyTorch, scikit-learn, or HuggingFace for model integration and debuggingNice to HavesExperience with vector search engines and embedding pipelines.Knowledge of advanced model serving patterns and asynchronous inference.Prior experience in manufacturing, retail, or finance sectors.