Job Description
- Architect, develop, and maintain high-performance Python applications supporting AI and machine learning use cases.
- Lead peer code reviews and enforce best practices in software engineering and coding standards.
- Design, build, and manage ELT/ETL data pipelines in massively parallel processing environments (e.g. Spark, Ray, or similar).
- Oversee the full machine learning model lifecycle, including deployment, monitoring, optimisation, and maintenance.
- Implement automated monitoring, alerting, and reliability mechanisms for production ML systems.
- Mentor junior developers and data scientists on Python development and engineering best practices.
- Collaborate with stakeholders to translate business and analytical requirements into robust technical solutions.
- Contribute to improving system performance, scalability, and operational resilience.
What we are looking for:
- BSc in Computer Science or a related field ( *Transcripts Required)
- 5+ years’ experience in Python development with strong software engineering fundamentals.
- Proven experience building and supporting production-grade systems.
- Strong understanding of software design principles, including SOLID principles.
- Experience with CI/CD pipelines, Git, and unit testing frameworks.
- Hands-on experience with MLOps tools such as MLflow, Kubeflow, or similar platforms.
- Strong knowledge of cloud platforms such as AWS, Azure, or GCP.
- Ability to debug complex systems and deliver scalable, maintainable solutions.
- Strong collaboration and communication skills with the ability to work across technical and business teams.
- Ownership mindset with a focus on system reliability, performance, and continuous improvement.
Advantageous experience:
- Exposure to tools such as Vertex AI, BigQuery, and Cloud Composer.
- Experience working in large-scale data environments and distributed systems.
Please note that if you do not hear from us within 3 weeks, consider your application unsuccessful.
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