Role : 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.