Software Engineer (Machine Learning) (Cybersecurity)

Location: UK, with roles based in London, Manchester, or Bath; hybrid and flexible working options are available.

Company

hirify.global develops cybercrime detection and disruption technology that protects organizations and governments from phishing, online scams, and other cyberattacks.

What you will do

• Build, evaluate, and tune machine learning classifiers used to block fraudulent content and coordinate takedowns.
• Deploy and operate model-serving infrastructure on Kubernetes, including LLM inference with tools such as vLLM.
• Optimize models for high-volume, cost-efficient serving and integrate them into production classification platforms.
• Run experiments against live data, measure precision, recall, and false-positive rates, and use results to determine what ships.
• Build model pipelines and monitoring for feature extraction, scheduled retraining, experiment tracking, and operational metrics.
• Investigate production issues, including model regressions and performance bottlenecks, while collaborating with engineers and analysts.

Requirements

• Strong understanding of HTTP, DNS, and how websites work from request to rendered page.
• Working knowledge of machine learning fundamentals, including training, evaluation, overfitting, and precision/recall trade-offs.
• Empirical approach to designing experiments, measuring outcomes, and validating impact with metrics.
• Strong written and verbal communication, attention to detail, and responsibility for the accuracy of customer-facing classifications.
• Willingness to learn Go and modern Perl, including asynchronous programming.
• Based in the UK, preferably London, with Manchester and Bath also available.

Nice to have

• Interest in cybercrime or cybersecurity.
• Experience fine-tuning and evaluating models, including LLM agents and model serving with vLLM or llama.cpp.
• Experience with multimodal models, embeddings, similarity search, Kubernetes, Flux, Argo, API gateways, MLflow, or Argo Workflows.
• Experience with SQL databases and query optimization against large datasets.

Culture & Benefits

• Hybrid and flexible working options with meals, snacks, and drinks provided in the office.
• 33 days of annual leave, including public holidays, plus enhanced family leave and company sick pay.
• Salary sacrifice pension with matched employer contributions up to 5%, private health cover, and life assurance at four times salary.
• Equity tracking scheme, spot rewards, and an employee referral bonus scheme.
• Two paid learning and development days annually, access to Udemy and Coursera, and two paid volunteering days.
• Health, safety, and wellness support available 24/7, with an inclusive workplace and hiring-process adjustments available.