Senior AI/ML Engineer – Platform Architecture (MLOps & Production AI Focus)

<p>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.</p><h3><strong>Role Overview</strong></h3><p>We are seeking a <strong>Senior AI/ML Engineer</strong> 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.</p><p>The ideal candidate will bring <strong>deep expertise in MLOps</strong>, <strong>neural network development</strong>, and a <strong>track record of delivering AI solutions into production environments</strong>. Your work will directly contribute to enabling a no-code AI ecosystem through modular, plug-and-play ML components.</p><h3><strong>Key Responsibilities</strong></h3><ul> <li><p><strong>Design and implement reusable, production-grade ML modules</strong> (e.g., neural networks, regression, classification) for integration into a no-code rApp platform.</p></li> <li><p><strong>Lead MLOps strategy</strong>: establish scalable model lifecycle management including versioning, deployment pipelines, and monitoring.</p></li> <li><p>Build seamless model training workflows integrated with telecom PM counters, KPIs, and pre-processing logic.</p></li> <li><p>Drive the creation of training pipelines, evaluation frameworks, and hyperparameter tuning mechanisms with clear metrics and iteration tracking.</p></li> <li><p>Develop and enforce <strong>robust data ingestion and pre-processing pipelines</strong>, ensuring clean, real-time, and reproducible data for model training and inference.</p></li> <li><p>Support integration of trained models into <strong>closed-loop automation systems</strong>, enabling intelligent network functions.</p></li> <li><p>Collaborate with DevOps, Backend, and UX teams to expose ML capabilities through intuitive interfaces and microservices.</p></li> <li><p>Champion best practices in AI/ML development—testing, explainability, observability, and governance.</p></li> </ul><h3><strong>Required Skills and Experience</strong></h3><p><strong>Must-Haves:</strong></p><ul> <li><p>5+ years of experience in AI/ML engineering with a strong emphasis on <strong>end-to-end delivery into production environments</strong>.</p></li> <li><p>Proven hands-on experience in <strong>MLOps</strong>, including automated pipelines, CI/CD integration, model serving, and monitoring (preferably on <strong>Google Cloud Platform</strong> using tools like Vertex AI, BigQuery ML).</p></li> <li><p>Deep knowledge of <strong>neural networks and traditional ML models</strong> (e.g., time-series, classification, regression) with demonstrated applications in production settings.</p></li> <li><p>High proficiency in <strong>Python</strong>, with experience building scalable, API-driven microservices.</p></li> <li><p>Experience deploying containerised ML services using <strong>Docker</strong>, with strong familiarity with CI/CD workflows.</p></li> <li><p>Expertise in <strong>model validation, tuning</strong>, metadata tracking, and training history.</p></li> </ul><p><strong>Nice-to-Haves:</strong></p><ul> <li><p>Experience with <strong>no-code/low-code ML platforms</strong> or visual ML tooling.</p></li> <li><p>Strong stakeholder management and interpersonal skills.</p></li> <li><p>Exposure to <strong>telecom domain standards</strong>, including O-RAN or PM/KPI systems.</p></li> <li><p>Familiarity with <strong>Kafka</strong>, <strong>AVRO</strong>, and stream processing for real-time AI use cases.</p></li> <li><p>Experience integrating AI pipelines into <strong>observability and monitoring</strong> platforms.</p></li> <li><p>Previous involvement in <strong>closed-loop automation</strong> projects or intelligent rApp systems.</p></li> <li><p>Experience within the Telecomms industry</p></li> </ul><h3><strong>What We Offer</strong></h3><ul> <li><p>A pivotal role in building next-generation AI solutions for the telecom industry, with opportunities to influence platform direction and lead innovation.</p></li> <li><p>Collaboration with a highly motivated, forward-thinking team committed to pushing the boundaries of what AI can do in telecom.</p></li> <li><p>Competitive compensation including health benefits, retirement plans, and performance bonuses.</p></li> <li><p>A culture of inclusivity, growth, a