Senior ML Engineer

Congruity360; Belfast City District; Hybrid; GBP 85,000 - 110,000; Full time

Benefits offered by this job

Pension scheme

Flexible hours

Health insurance

Generous holiday leave

Volunteer policy

Hybrid work options

Job summary

Congruity360 in Belfast, Northern Ireland, is seeking a Senior ML Engineer to join a fast-moving engineering team. You will contribute to a new cybersecurity product line, applying advanced machine learning to detect anomalies and drive real-time decisions.

The role requires a strong background in Java, distributional statistics, unsupervised methods, and experience with feature computation on columnar stores. You’ll collaborate with a cross-functional team and grow our data-driven solutions.

Qualifications

• Bachelor's or higher in Mathematics, Physics, Statistics or related quantitative field.
• 5+ years of software engineering and development experience.
• Strong communication, detail-orientation, and self-motivation are essential.

Responsibilities

• Develop and deploy ML solutions in production services.
• Lead technical decisions within the team and collaborate with colleagues.
• Build high-quality software to enable secure data governance and cybersecurity features.
• Work closely with data engineers to implement feature computation from columnar stores.

Skills

Java production services

Statistical anomaly detection

Unsupervised learning (IsolationForest

Feature computation on columnar stores

Data modeling & analysis

Education

University degree in Mathematics, Physics, Statistics

Tools

Commons Math

Smile

XGBoost4J

ojAlgo

Job description

Job Title: Senior ML Engineer

Department: Engineering

Reports To: Team Lead

Working Pattern: Hybrid – minimum 2 day per week in Belfast office

Location: Belfast, Northern Ireland (Role is NI based. Candidate must have right to live and work in UK)

Salary: Negotiable

Company background:

Congruity360 is headquartered in Boston with employees across the US, England and Northern Ireland. The Congruity360 flagship product, Classify360, enables clients to reduce their financial and data risk by increasing their data understanding, classification, and security, allowing clients to meet all of the current, new, and changing laws, regulations, and business drivers. In other words, making intelligent business decisions.

Job Summary:

A new product offering is emerging from concept phase, which expands our solution set from compliance and data governance into cybersecurity.

This role offers the opportunity to work in emerging technologies with a primary focus on a machine learning skillset. The successful candidate will be an integral part of a dynamic team, working in a fast-paced development environment, generating creative solutions to solve customer needs and challenges. The successful candidate will be actively involved in driving technical decisions within the team, with a desire to produce high quality software to provide a superior client experience.

Education requirements:

• A University degree (or equivalent) in Mathematics, Physics, Statistics or equivalent applied quantitative background

Experience:

• 5+ years relevant software engineering and development experience
• Proactive attitude with great communications skills, attention to detail, self-motivated, and the ability to work well with people are essential

Essential Criteria:

• 5+ years Java in production services
• Hands-on statistical anomaly detection: distribution divergence, robust z-scores, EMD, baseline/drift methods
• Unsupervised methods (Isolation Forest or similar) and their evaluation without labels
• Implementing numerical work in Java (Commons Math, Smile, XGBoost4J, ojAlgo or similar)
• Working directly against columnar stores for feature computation

Desired Criteria:

• UEBA, fraud, or telemetry scoring experience
• Multi-signal corroboration / ensemble scoring design
• Gradient-boosted meta-models once labels exist
• Security domain familiarity
• System Integration
• Agile development

Company Benefits:

• Pension scheme.
• Flexible working hours and hybrid work options.
• Health insurance and wellness programs.
• Generous holiday leave and paid time off.
• Flexible working policy
• Volunteer policy