Senior Ai/Ml Engineer – Platform Architecture

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 Overview
We 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 Responsibilities
Design 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 Experience
Must-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 industry
What We Offer
A 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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