Senior Machine Learning Engineer

Senior Machine Learning Engineer

Location: Ireland (Remote-Friendly / Occasional Dublin Office Visits)

Salary: €120,000 - €130,000+ DOE

Employment Type: Permanent

Industry: Cybersecurity / AI / Predictive Analytics

The Opportunity

MCS Group is delighted to be partnering with an innovative, growing Irish technology company as they look to appoint a Senior Machine Learning Engineer to become their first dedicated ML hire.

This is a particularly exciting opportunity for an experienced ML Engineer or technically strong Data Scientist who wants to move beyond working on individual models and take genuine ownership of how machine learning is developed, deployed and used within a product.

The business operates in the cybersecurity space and has spent years building an extensive dataset covering vulnerabilities, exploits, threat activity and historical security intelligence.

Having already invested in research and early proof-of-concept work, the company is now entering an exciting new phase of development.

The ambition is to move beyond understanding existing threats and towards predicting what might happen next.

Rather than joining an established ML department with predefined processes and narrowly scoped responsibilities, you'll have the opportunity to shape how machine learning is applied across the product, working closely with an experienced engineering team to turn complex data into genuinely valuable customer-facing functionality.

This is a hands-on engineering position with significant autonomy, technical ownership and the opportunity to make a lasting impact.

What You'll Do

As the company's first dedicated Machine Learning Engineer, you'll take ownership of developing and delivering predictive ML capabilities, from initial problem definition through to production.

Your responsibilities will include:

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Working with engineering and product stakeholders to identify opportunities where machine learning can solve meaningful customer problems.

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Exploring and analysing large, complex historical datasets to identify patterns, relationships and predictive signals.

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Translating loosely defined business challenges into structured machine learning problems.

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Designing, developing and evaluating predictive models, including classification, risk scoring, anomaly detection and other relevant approaches.

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Taking ownership of feature engineering, model selection, experimentation and evaluation.

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Developing robust approaches to handling incomplete, imperfect and potentially unlabelled datasets.

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Building and deploying production-ready ML solutions that integrate effectively with existing software products.

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Establishing appropriate approaches to model monitoring, performance evaluation, drift detection and retraining.

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Collaborating with software engineers to ensure ML capabilities are scalable, reliable and maintainable.

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Making independent technical decisions and communicating the reasoning behind modelling approaches and trade-offs.

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Helping establish practical ML engineering standards and best practices as the company's capabilities develop.

What You'll Bring

We're looking for someone with strong technical foundations who can also operate independently, particularly when the problem or solution isn't clearly defined from the outset.

Essential experience:

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Significant commercial experience in Machine Learning Engineering, Applied Machine Learning or Data Science, ideally within product-focused environments.

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Strong Python programming skills and experience developing production-quality ML solutions.

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Excellent understanding of traditional and predictive machine learning techniques, including classification, regression, risk scoring, anomaly detection and feature engineering.

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Experience with relevant ML frameworks such as scikit-learn, XGBoost, LightGBM, PyTorch or TensorFlow.

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Proven experience taking machine learning solutions beyond experimentation and into real production environments.

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Strong understanding of the end-to-end ML lifecycle, including problem definition, data preparation, modelling, evaluation, deployment and monitoring.

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Experience working with complex, imperfect or large-scale datasets.

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Ability to independently investigate ambiguous problems, determine an appropriate technical approach and deliver practical solutions.

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Strong communication skills, with the ability to explain technical decisions and trade-offs to both technical and non-technical stakeholders.

Most importantly, we're looking for someone who can demonstrate genuine end-to-end ownership of ML projects, rather than simply contributing to one stage of an established process.

Nice to Have

Experience in any of the following would be particularly valuable:

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Previous experience as an early or founding ML hire within a startup or scale-up.

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Experience developing predictive models in cybersecurity, fraud detection, financial risk, behavioural analytics or other data-intensive industries.

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Familiarity with MLOps practices, model versioning, experiment tracking and automated retraining.

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Experience with tools such as MLflow, FastAPI, Docker, Kubernetes or cloud-based ML services.

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Knowledge of temporal modelling, time-series analysis or probabilistic modelling.

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Experience working with highly imbalanced datasets or problems where labels and ground truth are difficult to establish.

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Previous experience helping transition ML research or proof-of-concept projects into commercial products.

Cybersecurity experience is not essential. The business is particularly interested in strong machine learning problem-solvers who can apply their experience to a new and interesting domain.

How We Work

This is a relatively early-stage technology business with an experienced engineering team, a strong technical product and ambitious plans for the next stage of growth.

The environment is collaborative, pragmatic and focused on building technology that solves real problems.

You'll be trusted to take ownership of your work, challenge assumptions and make technical decisions without unnecessary layers of management.

The company operates a remote-friendly working model, with occasional collaboration in Dublin. There is flexibility for candidates based elsewhere in Ireland who can travel when required.

This opportunity would particularly suit someone who enjoys working in smaller, highly capable teams where individual contributions can make a significant difference.

What's on Offer?

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Salary of €120,000 - €130,000+, with flexibility depending on experience.

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Equity/share options.

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Pension.

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Remote-friendly working arrangements.

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The opportunity to become the company's first dedicated ML hire.

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Genuine autonomy and ownership of technically challenging machine learning problems.

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Access to substantial real-world datasets with significant predictive potential.

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The opportunity to take existing research and early-stage ML work into production.

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Close collaboration with an experienced engineering and product team.

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The chance to help shape the future direction of machine learning within a growing Irish technology business.

Hiring Process

The interview process includes an initial discussion followed by a practical technical assessment and review.

The assessment is designed to understand how you approach real-world machine learning challenges, including modelling decisions, evaluation, production considerations and technical trade-offs.

The company has an active requirement and is keen to move efficiently with suitable candidates.

How to Apply

To apply for this role, submit your CV via the application form provided. Alternatively, to speak in absolute confidence about this opportunity, please contact Jack Tyrrell via j.tyrrell@mcsgroup.jobs

Disclaimer

If you have a disability which means you require assistance at any stage of the recruitment process, please contact us directly to discuss. We are committed to providing equality of opportunity to all.

Please note, we are receiving an exceptionally high number of applications at present and will be unable to shortlist candidates who are not meeting the specific requirements for this role. Due to the high volume of applications, we may be unable to provide individual feedback. We thank you in advance for your understanding.