1. Roles & Responsibilities: 2/10  
2. Years of Experience: 10/10  
3. Education Qualification: 0/10  
4. Skills/Knowledge: 2/10  
5. Domain/Industry: 6/10  
6. Key Competencies: 4/10  
7. Certifications: 0/10  

<h5 style="font-family: Roboto; font-size: 0.88rem;"><b>Overall Summary</b></h5>
<ol style="font-family: Roboto; font-size: 0.88rem;">
  <li>The candidate demonstrates over 12 years of experience in AI/ML, which aligns well with the required 8–12 years of experience. This is clearly stated in the summary and supported by the professional timeline.</li>
  <li>However, the resume lacks direct alignment with the core roles and responsibilities outlined in the job requirements. There is no mention of building or maintaining MLOps pipelines, no reference to GCP or Vertex AI, and no indication of model lifecycle management, real-time monitoring, or drift detection. The projects described are more focused on AI application development and voice agents rather than MLOps infrastructure.</li>
  <li>There is no education information provided in the resume. No degrees, institutions, or academic background is mentioned, which is a critical gap for evaluation.</li>
  <li>In terms of skills and knowledge, the resume does not mention key technologies such as GCP, Vertex AI, TensorFlow, CUDA, or TFX. While the candidate demonstrates experience in AI and ML applications, there is no evidence of using Python 3.10, pandas, NumPy, or any ML workflow orchestration frameworks. The focus is more on application-level AI solutions rather than infrastructure-level MLOps capabilities.</li>
  <li>The domain experience appears to be within the broader Information Technology space, particularly in AI/ML solution architecture. However, the absence of cloud platform experience (especially GCP) and MLOps-specific tools limits the domain relevance.</li>
  <li>Key competencies such as problem-solving and working in fast-paced environments are implied through the complexity and scale of projects. However, there is no explicit or implicit evidence of experience in automating ML workflows, ensuring scalability/security/high availability, or collaborating with cross-functional teams in an MLOps context.</li>
  <li>No certifications are listed in the resume. There is no mention of any credentials related to GCP, MLOps, Python, TensorFlow, or other relevant technologies, which is a significant shortfall given the technical nature of the role.</li>
</ol>