Visionary Machine Learning Specialist

2 days ago

Pune, Maharashtra, India beBeeArtificial Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
AI Engineer

We are seeking a skilled AI professional with expertise in machine learning, natural language processing, and workflow automation.

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

As an AI engineer, you will work at the intersection of large language models, workflow orchestration, and classical machine learning models to improve how alerts are prioritized, classified, and contextualized.

Key responsibilities include designing, implementing, and optimizing ML models for tasks such as prioritization, ranking, clustering, anomaly detection, and classification.

  • Design, implement, and optimize machine learning models using techniques like retrieval-augmented generation, prompt engineering, and fine-tuning.
  • Develop agentic workflows for investigation, classification, and automated response in cybersecurity.

Requirements:

  • 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).
  • 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 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 environment.

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