Job Description:
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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 Why developers apply for opportunities like this: 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 #J-18808-Ljbffr
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