Pratyush kumar Sahu

ML Engineer

https://www.opentalent.in/pratyush-kumar-sahu

KIIT Deemed University Bhubaneswar

Key Strengths

Strong foundational knowledge and practical experience in Machine Learning, Deep Learning, and Natural Language Processing, demonstrated through projects (unsupervised time-series anomaly detection, TensorFlow-based image classification, LLM/OCR integration, MLOps pipelines).
Proficiency in MLOps tools and practices (MLflow, FastAPI, Docker, AWS Lambda) for deploying scalable ML solutions with a focus on low-latency inference.
Full-stack development capabilities (React, Node.js, JavaScript) for integrating AI models into end-to-end applications and building interactive dashboards.
Experience with data visualization tools (Power BI, Tableau) and various databases (MySQL, MongoDB, PostgreSQL) for data engineering and reporting.
Certifications in Oracle OCI Data Science, Udemy Complete Data Science, ML, DL, NLP, IBM Business Analytics, and AWS Cloud Foundations indicate a proactive learning approach and commitment to the field.
The candidate's project portfolio and stated skills strongly align with the requirements of an ML Engineer role, particularly one involving end-to-end model development, deployment, and integration.

Cultural & Operational Fit

Cultural Fit Analysis

Based on the provided psychometric test score of 0, there is no positive indication of cultural fit regarding logical reasoning, work attitude, stress handling, or team collaboration. This score suggests a significant mismatch or a critical failure in the assessment. While the Project Lead role in NSS demonstrates leadership and teamwork in a community context, it cannot override the explicit psychometric test result for professional cultural fit assessment.

Soft Skills & Operational Fit

The 'Project Lead' role in the National Service Scheme suggests leadership, organizational, and teamwork skills, including planning, execution, delegation, and coordination. The professional summary indicates a results-oriented mindset with a focus on operational efficiency. However, the psychometric test score of 0 raises significant concerns regarding logical reasoning, work attitude, stress handling, and team collaboration, which are critical for operational fit.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Key Strengths

Strong foundational knowledge and practical experience in Machine Learning, Deep Learning, and Natural Language Processing, demonstrated through projects (unsupervised time-series anomaly detection, TensorFlow-based image classification, LLM/OCR integration, MLOps pipelines).
Proficiency in MLOps tools and practices (MLflow, FastAPI, Docker, AWS Lambda) for deploying scalable ML solutions with a focus on low-latency inference.
Full-stack development capabilities (React, Node.js, JavaScript) for integrating AI models into end-to-end applications and building interactive dashboards.
Experience with data visualization tools (Power BI, Tableau) and various databases (MySQL, MongoDB, PostgreSQL) for data engineering and reporting.
Certifications in Oracle OCI Data Science, Udemy Complete Data Science, ML, DL, NLP, IBM Business Analytics, and AWS Cloud Foundations indicate a proactive learning approach and commitment to the field.
The candidate's project portfolio and stated skills strongly align with the requirements of an ML Engineer role, particularly one involving end-to-end model development, deployment, and integration.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Pratyush kumar Sahu

Key Strengths

Cultural & Operational Fit

Skills

Education

Key Strengths

Cultural & Operational Fit