ML Engineer for Secure AI & LLM Pipelines

Ballistic Ventures; San Francisco (CA); On-site; USD 36,000 - 60,000; Full time

Job summary

Witness AI in Cairo is seeking a Machine Learning Engineer to design, build, and evaluate language models powering our AI security products. You’ll own the end-to-end ML pipeline from dataset curation to deployment, emphasizing reliability, interpretability, and safety.

The role blends engineering and applied research, requiring 2–5+ years in ML/data science, strong Python tooling, and experience with PyTorch, Spark/Kafka/Airflow, and cloud/container tech.

Qualifications

• 2–5+ years in ML or data science, ideally in security or infrastructure-heavy environments.
• Strong software engineering background (Python), including testing and CI/CD.
• Proficiency in PyTorch and ML fundamentals (supervised/unsupervised, NLP).
• Experience with data engineering tools (Spark, Kafka, Airflow).
• Familiarity deploying models on cloud platforms (AWS/GCP/Azure) and containerized environments (Docker, Kubernetes).
• Interest or background in cybersecurity, adversarial ML, or anomaly detection.

Responsibilities

• Build scalable pipelines to collect, preprocess, and manage datasets for training and evaluation of LLMs.
• Design and run experiments to evaluate LLMs on accuracy, robustness, fairness, and safety.
• Create dashboards, reports, and visualizations to communicate evaluation results.
• Develop knowledge graphs to structure data and improve context-driven model performance.
• Collaborate with researchers and data scientists to integrate ideas into engineering workflows.
• Fine-tune and integrate models into production with reliable, scalable, CI/CD-friendly approaches.
• Contribute to ML tooling and experimentation frameworks to accelerate iteration.

Skills

Python

PyTorch

CI/CD

Testing (pytest)

Spark

Kafka

Airflow

Cloud platforms

Docker

Kubernetes

NLP

ML fundamentals

Tools

Docker

Kubernetes

Spark

Airflow

Kafka

Job description

Witness AI in Cairo is seeking a Machine Learning Engineer to design, build, and evaluate language models powering our AI security products. You’ll own the end-to-end ML pipeline from dataset curation to deployment, emphasizing reliability, interpretability, and safety.

The role blends engineering and applied research, requiring 2–5+ years in ML/data science, strong Python tooling, and experience with PyTorch, Spark/Kafka/Airflow, and cloud/container tech.