SSE- AI

Job description

**Software Engineer – AI** **About Netcore UNBXD** Netcore Cloud is a global Martech and Product Discovery leader, enabling brands to deliver intelligent, hyper-personalized customer experiences at scale. Our platform processes billions of events daily, combining advanced data engineering, real-time decisioning, and machine learning to power high-performance SaaS solutions used by thousands of enterprises worldwide. We operate at the intersection of distributed systems, AI innovation, and large-scale infrastructure — solving complex engineering problems that directly impact global businesses. **The Opportunity** We are looking for a high-impact AI Engineer who thrives in solving large-scale data challenges. You will play a key role in architecting and building intelligent systems that power personalization, automation, and predictive insights across our Martech ecosystem. This role demands strong engineering fundamentals, system-level thinking, and a deep interest in scalable AI systems. **Key Responsibilities** - Architect and develop scalable, high-throughput Data and ML pipelines. - Design real-time and batch processing systems for large-scale event streams. - Build robust, production-grade ML workflows and inference systems. - Optimize distributed systems for performance, reliability, and cost efficiency. - Collaborate cross-functionally with Product, Analytics, and Platform teams to deliver intelligent features. - Contribute to system design discussions and drive engineering best practices. **Core Requirements** - Strong proficiency in **Java, Golang, or Python**. - Hands-on experience in **data engineering and ML systems development**. - Deep understanding of **distributed systems, scalability, and performance tuning**. - Experience with big data frameworks such as **Spark, Storm, or Apex**. - Strong foundation in data structures, algorithms, and system design. - Experience building production-ready systems in cloud environments. **Preferred Qualifications** - Experience with **Kafka, Hadoop, Hive, Vertica, or Spark Streaming**. - Exposure to containerization and orchestration tools like **Docker and Kubernetes**. - Familiarity with ML lifecycle tools such as **Kubeflow or AWS Batch**. - Experience with real-time personalization, recommendation systems, or predictive analytics. **What Makes This Role Exciting** - Work on AI systems operating at massive scale. - Influence architectural decisions in a rapidly growing SaaS company. - Solve real-world engineering challenges impacting global enterprises. - High ownership, high visibility, high growth.