Deskripsi Pekerjaan
Are you passionate about building the foundational infrastructure that fuels cutting-edge artificial intelligence? Neutron is seeking a highly skilled Data Scientist (AI Engineering) to join our innovative team in the heart of the Singapore River district. In this role, you will move beyond standard modeling to architect the robust data pipelines, scalable infrastructure, and machine learning frameworks that power our next-generation AI capabilities.
You will collaborate closely with cross-functional engineering teams to bridge the gap between complex research and production-grade software. We are looking for a technical visionary who thrives in a fast-paced environment and is dedicated to creating high-performance AI solutions that deliver real-world impact. If you are ready to architect the future of AI at Neutron, we want to hear from you.
Tanggung Jawab
- Design, build, and maintain scalable data pipelines to support complex AI and machine learning workloads.
- Develop high-performance infrastructure for model training, deployment, and real-time inference.
- Optimize existing AI workflows for maximum efficiency, latency, and throughput.
- Collaborate with data engineers and researchers to implement MLOps best practices across the product lifecycle.
- Automate data collection, processing, and feature engineering tasks to enhance model accuracy.
- Monitor and troubleshoot production AI systems to ensure 99.9% availability and high data integrity.
- Evaluate and integrate emerging AI tools and technologies to maintain Neutron's competitive edge.
Kualifikasi
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
- 3+ years of professional experience in data science, AI engineering, or backend software engineering.
- Proficiency in Python, C++, or Java, with a deep understanding of data structures and algorithms.
- Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization tools like Docker and Kubernetes.
- Expertise in SQL and NoSQL database management and large-scale data processing frameworks (e.g., Apache Spark, Kafka).
- Solid grasp of MLOps pipelines (MLflow, Kubeflow) and CI/CD methodologies.
- Excellent analytical, problem-solving, and communication skills to convey complex technical concepts to non-technical stakeholders.