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Artificial Intelligence Engineer
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Job Title: AI Engineer - Large Language Models
Description: We are seeking a highly skilled and experienced AI Engineer to join our team. The ideal candidate will have expertise in large language models (LLMs) and machine learning, with hands-on experience building intelligent systems that improve cybersecurity investigations, prioritization, and response.
Key Responsibilities:
- LLM Integration & Workflows: Develop and integrate LLMs into existing systems, designing agentic workflows for investigation, classification, and automated response.
- Machine Learning Development: Design, implement, and optimize ML models for prioritization, ranking, clustering, anomaly detection, and classification, applying techniques like Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning.
- Data Preparation & Feature Engineering: Collect, preprocess, and transform structured and unstructured data, including logs, text, and access patterns, engineering features to maximize model interpretability and performance.
- Model Training & Deployment: Train and evaluate models using rigorous metrics, optimizing hyperparameters and deploying ML and LLM models at scale into production with strong monitoring, drift detection, and observability.
- Collaboration: Work closely with data scientists, ML engineers, security researchers, and software teams to build end-to-end solutions, documenting models, workflows, and pipelines for reproducibility and knowledge sharing.
Requirements:
- A Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field.
- 5+ years of experience in ML/AI, with at least 3 years deploying production-grade systems.
- Strong knowledge of machine learning algorithms for classification, clustering, ranking, and anomaly detection.
- Proficiency with LLM frameworks and APIs (OpenAI, Hugging Face, LangChain, LlamaIndex).
- Hands-on experience building workflow automation with LLMs and integrating them into applications.
- Solid programming skills in Python (PyTorch, TensorFlow, scikit-learn).
- Knowledge of NLP tasks such as text classification, summarization, and semantic search.
- Experience with cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), and MLOps best practices.
- Strong problem-solving, analytical, and communication skills.
- The ability to thrive in a fast-paced, evolving startup environment.
Contact Information: Write to us to explore this opportunity.
