Senior AI/ML Engineer, Security Log Intelligence

United States Digital Space LLC; Berlin; Hybrid; EUR 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

Work from anywhere in Germany

Berlin office access

30 days paid time off

Deutschlandticket provided

Annual courses budget

Modern tooling and AI focus

Light process and clear communication

Zusammenfassung

United States Digital Space LLC is building AI-powered threat analysis tools inside the company platform. The Senior AI/ML Engineer will lead applied AI/ML work for parsing security logs and relating telemetry to known attacker activity.

The role focuses on LLMs, embeddings, retrieval, and deterministic heuristics with strict latency and deployment constraints. Fixed-term through Oct 31, 2027, with emphasis on production-grade results.

Qualifikationen

• Depth in ML/LLM systems and practical judgment valued over titles.
• Strong Python and software engineering skills for production systems.
• Experience with open-weight models, embeddings, retrieval pipelines, or similar.
• Experience fine-tuning, PEFT, quantisation, model serving, or inference optimization.
• Understanding of hallucination, calibration, distribution shift, and model failure analysis.
• Background in information retrieval, semantic retrieval, ranking, or extraction.
• Familiarity with evaluation methods like Recall@K, MRR, F1, exact match, calibration.
• Ability to build reproducible benchmarks and datasets.

Aufgaben

• Develop security-log parsing methods for heterogeneous telemetry.
• Design embeddings and retrieval strategies for security events.
• Implement confidence scoring and calibration for ambiguous evidence.
• Ground results in traceable evidence from telemetry.
• Define datasets, baselines, ablations, and metrics; analyze failures.
• Optimize inference for cloud and on-prem deployment.
• Productize methodologies with backend and integration engineers.
• Document experiments and architecture decisions.
• Contribute to academic publication as a co-author.

Kenntnisse

Machine Learning & LLM Systems

Python

PyTorch

Embeddings & Retrieval

Fine-tuning & PEFT

Calibration & Evaluation

Information Retrieval

Evaluation Metrics

Software Engineering

Research & Reading

English Proficiency

Ausbildung

MSc, PhD or equivalent research

Tools

PyTorch

Jobbeschreibung

We are building a new capability that turns fragmented, noisy security logs into explainable, AI-powered threat analysis, delivered inside the the company platform.

As Senior AI/ML Engineer at the company, you will lead the applied AI/ML work behind new analysis capabilities for our breach and attack emulation platform. The core challenge is extracting useful structure from heterogeneous, partially unstructured security telemetry and relating it to known attacker activity.

The problem is broader than prompt engineering. You will determine where LLMs, embeddings, retrieval, learned ranking, and deterministic heuristics are justified. The standard is measurable improvement against reproducible baselines, not architectural fashion. Everything you build must operate under realistic latency, reliability, and deployment constraints.

This is a fixed-term position running until 31 October 2027.

Tasks

• Develop Security-Log Parsing Methods: Design and implement methods for extracting typed events from heterogeneous SIEM, EDR, NDR, operating-system, and network telemetry.
• Design Embeddings and Retrieval: Select, evaluate, and tune representations and retrieval methods for security events.
• Handle Ambiguity Explicitly: Implement confidence scoring, calibration, and controlled treatment of ambiguous evidence.
• Ground Results in Evidence: Ensure that results are supported by traceable evidence from the original telemetry.
• Build Rigorous Evaluations: Define datasets, baselines, ablations, and metrics, and analyse failure modes systematically.
• Optimise Inference: Make the pipeline practical for cloud operation and on-premises deployment.
• Productise the Research: Work with backend, integration, and offensive-security engineers to turn experimental methods into maintainable services.
• Document the Work: Produce clear experiment records, architecture decisions, and technical reports.
• Contribute to Academic Research: Contribute, at minimum as a co-author, to an academic research paper published in the context of the project.

Requirements

You do not need to meet every requirement to apply. We care more about demonstrated depth, sound experimental judgement, and the ability to ship reliable systems than about a specific academic title.

• Machine Learning and LLM Systems
• Strong Python programming skills
• Practical experience with PyTorch or a comparable framework
• Experience with open-weight language models, structured outputs, embeddings, or retrieval systems
• Experience with fine-tuning, PEFT, quantisation, model serving, or inference optimisation
• Understanding of hallucination, calibration, distribution shift, and model failure analysis
• Information Retrieval and Evaluation
• Semantic retrieval, ranking, classification, or information extraction
• Approximate nearest-neighbour search and vector indices
• Evaluation using metrics such as Recall@K, MRR, F1, exact match, calibration, and ablation studies
• Dataset construction, partitioning, and reproducible benchmarking
• Software Engineering
• Ability to turn experimental code into maintainable production components
• Testing, profiling, observability, and performance analysis
• Experience working with APIs, distributed services, and containerised environments
• Cybersecurity Knowledge
• Security logs, SIEM, EDR, NDR, detection engineering, incident response, or threat hunting are strong advantages
• Understanding of endpoint, process, identity, and network telemetry is a plus
• Research Background
• MSc, PhD, or equivalent practical research experience in computer science, machine learning, data science, mathematics, or a related field
• Ability to read, reproduce, and critically evaluate current research
• Languages
• English (required)
• German (a plus)

Benefits

• Work from anywhere in Germany, and use our Berlin office as often as you like
• 30 days of paid time off, and a quiet inbox while you are away
• Company-paid Deutschlandticket
• Annual budget for the courses and certifications you pick yourself
• Modern tooling and extensive use of AI
• Light process, clear communication, focus on what really matters

We are an equal opportunity employer and welcome applications from all backgrounds and genders.

Questions about the role or the process are welcome at any point.

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