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SigniTeq - AI Analytics Engineer - Machine Learning Models

SigniTeq - AI Analytics Engineer - Machine Learning Models

Signiteq TechnologyPune
12 days ago
Job description

About the Job :

Location : Pune / Hyderabad / Bangalore.

Experience : 7-8 years.

Job Summary :

We are seeking an experienced AI Analytics Engineer with strong expertise in Azure DevOps to design, implement, and optimize data pipelines, machine learning models, and analytics solutions.

The ideal candidate will bridge the gap between data science, engineering, and DevOps practices to deliver scalable and production-ready AI / ML solutions.

Key Responsibilities :

  • Design, develop, and deploy AI / ML models and analytics workflows.
  • Build and manage end-to-end CI / CD pipelines in Azure DevOps for data and ML projects.
  • Automate data ingestion, preprocessing, model training, testing, and deployment.
  • Monitor model performance and implement retraining pipelines.
  • Work closely with data scientists, data engineers, and business stakeholders to translate requirements into scalable solutions.
  • Ensure solutions are secure, cost-optimized, and highly available on Azure.
  • Perform root cause analysis and continuous improvement for production issues.

Required Skills & Experience :

  • Hands-on experience with Azure DevOps (pipelines, repos, artifacts, boards).
  • Strong programming skills in Python or R for AI / ML development.
  • Experience with Azure Machine Learning, Databricks, Synapse, Data Factory.
  • Good understanding of MLOps principles and tools.
  • Strong knowledge of data visualization and analytics (Power BI a plus).
  • Familiarity with containerization (Docker, Kubernetes) for deploying ML workloads.
  • Experience with version control (Git) and agile development practices.

    • Preferred Qualifications :

  • Certification in Microsoft Azure AI Engineer Associate or Azure DevOps Engineer Expert.
  • Knowledge of LLMOps (large language model operations) and generative AI solutions.
  • Experience with monitoring and logging tools (e.g., Application Insights, Prometheus, ELK stack).
  • Strong problem-solving skills and ability to work in a fast-paced environment.

    • Soft Skills :

  • Excellent communication and collaboration skills.
  • Ability to translate technical insights into business value.
  • Strong analytical thinking and attention to detail.

    • (ref : hirist.tech)

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