Job Description:
The successful candidate will join a specialised team focused on developing machine learning and AI-driven capabilities that deliver valuable insights from large-scale, real-time distributed systems
Key responsibilities include:
- Designing and implementing machine learning and AI features from concept through deployment
- Working across the full product lifecycle, from idea generation and design to implementation and deployment
- Training, deploying, and supporting machine learning models in production environments
- Building software solutions capable of processing and analysing large-scale datasets
- Collaborating with software engineers, data specialists, and cross-functional teams to solve complex technical challenges
- Contributing to scalable, distributed systems and microservice-based architectures
- Ensuring solutions are practical, maintainable, and valuable to both end users and support teams
- Contributing to an engineering culture centred around innovation, learning, knowledge sharing, and technical excellence
- Exposure to petabyte-scale data environments
- The opportunity to work at the intersection of Software Engineering, AI, and Data Science
- Strong focus on mentorship, skills development, and continuous learning
- Hybrid working model that supports flexibility and work-life balance
- The ability to influence products from conception to deployment rather than working on isolated components
Skills & Experience:
Required:
- Minimum 3 years of hands-on experience in Data Science or a data-focused software engineering role
- Proven experience training, deploying, and supporting machine learning or AI models in production environments
- Strong programming ability in Python and/or Java
- Strong SQL and database design skills with experience working on large datasets
- Experience with data wrangling, feature engineering, and model evaluation
- Experience working in Unix-based environments, including scripting, networking, and troubleshooting
- Experience with version control systems, containers, CI/CD processes, and microservice architectures
Advantageous:
- Master's degree in a relevant field
- Experience with Apache Kafka or real-time event processing
- Strong understanding of distributed systems and scalability challenges
- Experience with NLP, LLMs, RAG architectures, or audio processing
- Experience deploying ML services as scalable microservices.
- Leadership or mentoring experience
- Exposure to telecommunications, signal processing, or IP networking
Qualification:
- Bachelor's Degree in Data Science, Computer Science, Engineering, Applied Mathematics, or a related quantitative discipline
- Minimum 3 years of relevant Data Science or Software Engineering experience
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