Senior Associate

Roles and responsibilities

This role is pivotal in driving the adoption and optimization of Azure AI and Machine Learning services within an organization. The individual will be responsible for the management and support of these services, ensuring their seamless operation, performance, and alignment with business objectives.

Key Responsibilities

• Service Management:
  • Overseeing the lifecycle of Azure AI and Machine Learning services, including planning, deployment, configuration, monitoring, and optimization.
  • Ensuring high availability, performance, and scalability of AI/ML services.
  • Developing and maintaining detailed documentation of service configurations and procedures.
• Technical Support:
  • Providing technical support and troubleshooting for AI/ML-related issues.
  • Collaborating with data scientists, developers, and business users to resolve problems efficiently.
  • Identifying and implementing solutions to improve service performance and reliability.
• Infrastructure Management:
  • Managing the underlying infrastructure for AI/ML workloads, including compute resources, storage, and networking.
  • Optimizing resource utilization to maximize cost-efficiency.
  • Implementing disaster recovery and business continuity plans.
• Model Deployment and Management:
  • Deploying and managing AI models into production environments.
  • Monitoring model performance and retraining as needed.
  • Integrating AI models into business applications and processes.
• Team Collaboration:
  • Collaborating with data scientists, engineers, and business stakeholders to understand their needs and requirements.
  • Providing guidance and expertise on AI/ML technologies and best practices.
  • Fostering a culture of innovation and experimentation within the team.
• Stay Updated:
  • Keeping abreast of the latest advancements in AI and Machine Learning.
  • Evaluating new technologies and tools to improve service capabilities.
  • Sharing knowledge and insights with the team through training and presentations.

Desired candidate profile

• Required Skills and Experience
• Strong understanding of Azure AI and Machine Learning services, including Azure Machine Learning, Cognitive Services, and Azure Databricks.
• Proficiency in Python, R, or other programming languages used for data science and machine learning.
• Experience with cloud computing platforms and infrastructure.
• Knowledge of data engineering and data pipeline development.
• Strong problem-solving and troubleshooting skills.
• Excellent communication and interpersonal skills.
• Ability to work independently and as part of a team.
  
  

Desired Qualifications

• Certifications in Azure AI and Machine Learning.
• Experience with specific AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, Scikit-learn).
• Knowledge of DevOps practices and tools.
• Experience with MLOps and model lifecycle management.

  Additional Information:

• Location: [Office location or remote options]
• Compensation: [Salary range or "competitive salary"]
• Benefits: [Details about health insurance, retirement plans, etc.]