Junior AI/ML Engineer, Data and Evaluation

Job description

We are building a new capability that turns fragmented, noisy security logs into explainable, AI-powered threat analysis, delivered inside the RedMimicry platform. As an AI/ML Engineer at RedMimicry, you will build the datasets, benchmarks, and evaluation infrastructure behind our applied AI/ML work on security telemetry. The quality of this work depends on accurate ground truth, disciplined data handling, reproducible experiments, and systematic error analysis. Your work will determine whether reported improvements are real and whether regressions are caught before deployment. You will work closely with the Senior AI/ML Engineer and Offensive Security Engineer. This role is suitable for an early-career or intermediate engineer with strong programming and data skills who wants to work on applied AI in a technically demanding cybersecurity environment. This is a fixed-term position running until 31 October 2027. Tasks Curate Security Datasets: Prepare telemetry from controlled engagements and test environments. Build Ground Truth: Create and maintain labelled examples, annotation guidelines, and consistency checks. Maintain Evaluation Partitions: Separate training, validation, and test data along relevant dimensions. Automate Benchmarks: Implement metrics and maintain reproducible benchmark and regression pipelines that run locally and in CI. Run Experiments and Error Analysis: Evaluate models and methods, and identify recurring failure modes and data-quality issues. Maintain Data Quality: Implement schema checks, provenance tracking, deduplication, validation, and dataset versioning. Document Experiments: Produce clear experiment records, plots, tables, and technical summaries that support engineering decisions. Requirements You do not need to meet every requirement to apply. Strong practical work, research projects, open-source contributions, or a relevant thesis can compensate for limited commercial experience. Programming and Data Work Good Python programming skills Experience with Pandas, NumPy, PyTorch, or similar tooling Ability to process structured and unstructured data reliably Familiarity with Git, automated tests, and reproducible development workflows Machine Learning and Evaluation Working understanding of supervised evaluation, train/test separation, and basic statistics Familiarity with language models, embeddings, retrieval, classification,…