AI Systems Developer

5 days ago

Aligarh, Uttar Pradesh, India beBeeArtificial Full time US$ 1,50,000 - US$ 2,50,000
Senior AI Engineer

This is a critical role that requires the expertise of a seasoned AI engineer to develop intelligent systems that enhance cybersecurity investigations, prioritization, and response. The successful candidate will have a strong background in building production-ready systems and will be able to combine their technical knowledge with hands-on experience to deliver high-quality solutions.

Key Responsibilities
  • LLM Integration & Workflows: Develop agentic workflows for investigation, classification, and automated response by integrating large language models into existing systems. Apply techniques like Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning.
  • Machine Learning Development: Design, implement, and optimize ML models for prioritization, ranking, clustering, anomaly detection, and classification using classical and modern architectures.
  • Data Preparation & Feature Engineering: Collect, preprocess, and transform structured and unstructured data to engineer features that maximize model interpretability and performance.
  • Model Training & Deployment: Train and evaluate models using rigorous metrics and deploy 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.
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.
  • Hands-on experience building workflow automation with LLMs and integrating them into applications.
  • Solid programming skills in Python.
  • Knowledge of NLP tasks such as text classification, summarization, and semantic search.
  • Experience with cloud platforms, containerization, and MLOps best practices.
  • Strong problem-solving, analytical, and communication skills.

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