Senior Azure Tech Lead

3 weeks ago

United Kingdom Kevin Edward Full time

About the Role :

Inside IR35

We are looking for a Senior Azure Tech Lead with expertise in Machine Learning (ML) and MLOps to guide the design and deployment of ML systems. This role combines hands-on engineering with strategic architectural leadership, ensuring our ML initiatives align with business goals.

Key Responsibilities :

  • Architectural Leadership :
  • Design scalable ML systems on Azure, ensuring performance and security.
  • Lead architecture discussions and guide ML and MLOps projects.
  • Promote the use of Azure-native tools to optimize workflows and modern MLOps practices.
  • Hands-on Engineering :
  • Develop and deploy ML models and pipelines, collaborating with data teams to automate processes.
  • Design data architectures for model training and real-time inference using Azure services.
  • Implement monitoring solutions for model performance and operational efficiency.
  • Collaboration & Leadership :
  • Work with cross-functional teams to integrate ML models into production.
  • Communicate complex concepts to technical and non-technical stakeholders.
  • Mentor junior engineers and data scientists.
  • Strategic Impact :
  • Define the ML and MLOps strategy, aligning it with business objectives.
  • Evaluate new tools and processes to enhance ML capabilities.

Required Skills & Experience :

  • 8+ years in IT with a focus on Azure architecture, Machine Learning, and MLOps.
  • Proficient in Azure services like Azure ML, AKS, Data Lake, and Synapse.
  • Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
  • Strong understanding of MLOps concepts, CI/CD, and model monitoring.
  • Proficient in Python, R, SQL, and containerization technologies (Docker, Kubernetes).
  • Experience with ETL/ELT processes and big data technologies (e.g., Apache Spark).
  • Proven leadership in complex technical environments with excellent communication skills.

Preferred Qualifications :

  • Azure certifications (e.g., Solutions Architect, Data Engineer, AI Engineer).
  • Experience with Agile/Scrum methodologies.
  • Knowledge of DevOps tools (Azure DevOps, Jenkins, GitLab) and edge computing for ML.

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