Zinkworks is a global leader in innovation, headquartered in Athlone, Ireland, with three office locations worldwide. We utilise the latest cutting-edge technologies to bring industry-leading expertise to our Telecommunication and Financial Services clients. We are adept at developing custom innovations that streamline our clients’ workflows and improve operational efficiency. With a commitment to quality and customer satisfaction, we have earned a reputation as a trusted partner for businesses seeking reliable software services.Role OverviewWe are seeking a Senior AI/ML Engineer to lead the design and delivery of the machine learning core that powers an AI app platform. This is a high-impact role focused on architecting a scalable system that enables users to build robust, AI-powered applications with minimal ML background. You will own the entire ML lifecycle—from data ingestion to model deployment—and will be critical in ensuring the system is production-ready, secure, and adaptable.The ideal candidate will bring deep expertise in MLOps, neural network development, and a track record of delivering AI solutions into production environments. Your work will directly contribute to enabling a no-code AI ecosystem through modular, plug-and-play ML components.Key ResponsibilitiesDesign and implement reusable, production-grade ML modules (e.g., neural networks, regression, classification) for integration into a no-code rApp platform.Lead MLOps strategy: establish scalable model lifecycle management including versioning, deployment pipelines, and monitoring.Build seamless model training workflows integrated with telecom PM counters, KPIs, and pre-processing logic.Drive the creation of training pipelines, evaluation frameworks, and hyperparameter tuning mechanisms with clear metrics and iteration tracking.Develop and enforce robust data ingestion and pre-processing pipelines, ensuring clean, real-time, and reproducible data for model training and inference.Support integration of trained models into closed-loop automation systems, enabling intelligent network functions.Collaborate with DevOps, Backend, and UX teams to expose ML capabilities through intuitive interfaces and microservices.Champion best practices in AI/ML development—testing, explainability, observability, and governance.Required Skills and ExperienceMust-Haves:5+ years of experience in AI/ML engineering with a strong emphasis on end-to-end delivery into production environments.Proven hands-on experience in MLOps, including automated pipelines, CI/CD integration, model serving, and monitoring (preferably on Google Cloud Platform using tools like Vertex AI, BigQuery ML).Deep knowledge of neural networks and traditional ML models (e.g., time-series, classification, regression) with demonstrated applications in production settings.High proficiency in Python, with experience building scalable, API-driven microservices.Experience deploying containerised ML services using Docker, with strong familiarity with CI/CD workflows.Expertise in model validation, tuning, metadata tracking, and training history.Nice-to-Haves:Experience with no-code/low-code ML platforms or visual ML tooling.Strong stakeholder management and interpersonal skills.Exposure to telecom domain standards, including O-RAN or PM/KPI systems.Familiarity with Kafka, AVRO, and stream processing for real-time AI use cases.Experience integrating AI pipelines into observability and monitoring platforms.Previous involvement in closed-loop automation projects or intelligent rApp systems.Experience within the Telecomms industryWhat We OfferA pivotal role in building next-generation AI solutions for the telecom industry, with opportunities to influence platform direction and lead innovation.Collaboration with a highly motivated, forward-thinking team committed to pushing the boundaries of what AI can do in telecom.Competitive compensation including health benefits, retirement plans, and performance bonuses.A culture of inclusivity, growth, and technological excellence—where your contributions directly shape real-world systems.
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