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Artificial Intelligence Engineer - NLP / LLM Models

Artificial Intelligence Engineer - NLP / LLM Models

CareerXperts ConsultingPune
30+ days ago
Job description

Job Description :

We are seeking a highly skilled and motivated AI Engineer with expertise in large language models (LLMs), AI workflows, and machine learning.

This role combines deep technical knowledge in ML / AI with hands-on experience building intelligent, production-ready systems that enhance cybersecurity investigation, prioritization, and response.

You will work at the intersection of LLM-driven automation, workflow orchestration, and classical ML models to improve how alerts are prioritized, classified, and contextualized reducing fatigue and enabling faster, more effective decision-making.

Your work will directly influence the development of agentic AI systems, workflow automation, and recommendation engines within cloud security Responsibilities :

LLM Integration & Workflows :

  • Build, fine-tune, and integrate large language models (LLMs) into existing systems.
  • Develop agentic workflows for investigation, classification, and automated response in cybersecurity.
  • Apply techniques like retrieval-augmented generation (RAG), prompt engineering, and fine-tuning for domain-specific tasks.

Machine Learning Development :

  • Design, implement, and optimize ML models for prioritization, ranking, clustering, anomaly detection, and classification.
  • Apply both classical forecasting models (AR, ARIMA, SARIMA, ES) and modern architectures (XGBoost, LSTM, DeepAR, N-BEATS, Temporal Fusion Transformer).
  • Data Preparation & Feature Engineering :

  • Collect, preprocess, and transform structured and unstructured data (including logs, text, and access patterns).
  • Engineer features to maximize model interpretability and performance.
  • Model Training, Evaluation, and Deployment :

  • Train and evaluate models using rigorous metrics (precision, recall, AUC, F1, etc.
  • Optimize hyperparameters and fine-tune LLMs for task-specific improvements.
  • Deploy ML / LLM models into production at scale with strong monitoring, drift detection, and observability.
  • Collaboration & Documentation :

  • Work closely with data scientists, ML engineers, security researchers, and software teams to build end-to-end solutions.
  • Document models, workflows, and pipelines for clarity, reproducibility, and knowledge :
  • Bachelors / Masters degree in Computer Science, AI / ML, Data Science, or a related field.
  • 5+ years of experience in ML / AI, including 3+ years deploying production-grade systems.
  • Experience contributing to publications (patents, libraries, or peer-reviewed papers) is a plus.
  • Strong knowledge of machine learning algorithms for classification, clustering, ranking, and anomaly detection.
  • Proficiency with LLM frameworks and APIs (OpenAI, Hugging Face Transformers, LangChain, LlamaIndex).
  • Hands-on experience building workflow automation with LLMs and integrating them into applications.
  • Solid programming skills in Python (experience with PyTorch, TensorFlow, scikit-learn).
  • Knowledge of NLP tasks (text classification, summarization, embeddings, semantic search).
  • Experience with recommendation systems or reinforcement learning is a strong plus.
  • Proven track record of deploying ML / AI models into production environments with scalability in mind.
  • Familiarity with cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes).
  • Understanding of MLOps best practices (CI / CD for ML, monitoring, retraining strategies).
  • Strong problem-solving and analytical mindset.
  • Excellent communication and teamwork skills.
  • Ability to work in a fast-paced, evolving startup environment.
  • (ref : hirist.tech)

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