Chief Machine Learning Architect

1 week ago

Bareilly, Uttar Pradesh, India beBeeDataScientist Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Senior Data Scientist Opportunity

We're looking for a highly skilled Senior Data Scientist to spearhead the development of agentic AI solutions.

This role involves designing and implementing large-scale machine learning architectures, leveraging natural language processing techniques to automate security decision-making and threat response. You will be responsible for operationalising LLMs, building agentic workflows, and deploying multi-agent systems for cybersecurity tasks.

Key Responsibilities:
  • Develop and deploy agentic AI systems for log analysis, anomaly detection, and incident response.
  • Create proof-of-concept GenAI solutions and evolve them into production-ready components using reusable best practices.
  • Implement CI/CD pipelines for model training, validation, and deployment with cloud-based tools.
  • Manage model versioning, set up automated testing, rollback procedures, and retraining workflows.
  • Automate cloud infrastructure provisioning and develop REST APIs and microservices containerised with cloud-native technologies.
  • Monitor models and infrastructure through cloud monitoring tools; analyse performance and optimise for cost and SLA compliance.
  • Collaborate with data scientists, application developers, and security analysts to integrate agentic AI into existing security workflows.
Qualifications:
  • Bachelor's or Master's in Computer Science, Data Science, AI or related quantitative discipline.
  • 4+ years of software development experience, including 3+ years building and deploying LLM-based/agentic AI architectures.
  • In-depth knowledge of generative AI fundamentals (LLMs, embeddings, vector databases, prompt engineering, RAG).
  • Hands-on experience with agentic frameworks and libraries.
  • Strong proficiency in Python and production-grade coding for data pipelines and AI workflows.
  • Deep MLOps knowledge: CI/CD for ML, model monitoring, automated retraining, and production-quality best practices.
  • Extensive cloud experience with cloud-based services.
  • Infrastructure as Code skills with cloud-native tools.
  • Experience building REST APIs, microservices, and containerization with cloud-native technologies.
  • Solid data science fundamentals: feature engineering, model evaluation, data ingestion.
  • Understanding of cybersecurity principles, SIEM data, and incident response.
  • Excellent communication skills for both technical and non-technical audiences.
Preferred Qualifications:
  • Cloud certifications.
  • Experience with workflow orchestration tools.
  • Familiarity with time series analysis, anomaly detection, and machine learning.

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