Dibyajyoti Ranjan SAHU

AI Engineer

https://www.opentalent.in/dibyajyoti-ranjan-sahu

Bāleshwar, Odisha, IndiaMember since November 20, 2025

Key Strengths

Strong foundational skills in VLSI design, EDA tools (Cadence, Synopsys, Vivado), Verilog/VHDL, and Python programming.
Demonstrated ability in data analysis using NumPy, pandas, and matplotlib, which is transferable to AI/ML data pipelines.
Initial exposure to TinyML model implementation and performance analysis on embedded devices, directly relevant to specialized AI engineering roles.
Experience with hardware-related projects (4-bit ALU, CMOS circuit design, SOI TFET simulation) could be an asset for hardware-accelerated AI or embedded AI systems.
Mentoring experience indicates leadership potential and ability to guide peers.

Cultural & Operational Fit

Cultural Fit Analysis

The psychometric test score of 0 is a critical red flag, indicating severe concerns regarding the candidate's work attitude, stress handling, and team collaboration. This score suggests a significant risk to cultural fit and requires immediate and thorough re-evaluation.

Soft Skills & Operational Fit

The psychometric test score of 0 raises significant concerns regarding logical reasoning, work attitude, stress handling, and team collaboration. While the resume mentions mentoring juniors, this positive indicator is heavily outweighed by the critical test result, suggesting a potential lack of operational fit without further assessment.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Experience

PMEC

Summer Trainee

June 4, 2025 – June 17, 2025

PMEC, Odisha, India

Indian Institute of Technology Tirupati

Summer Research Intern

May 1, 2024 – July 1, 2024

Chindepalle, Andhra Pradesh, India

IIRS

Summer Trainee

July 1, 2023 – August 1, 2023

Dehradun, Uttarakhand, India

Key Strengths

Strong foundational skills in VLSI design, EDA tools (Cadence, Synopsys, Vivado), Verilog/VHDL, and Python programming.
Demonstrated ability in data analysis using NumPy, pandas, and matplotlib, which is transferable to AI/ML data pipelines.
Initial exposure to TinyML model implementation and performance analysis on embedded devices, directly relevant to specialized AI engineering roles.
Experience with hardware-related projects (4-bit ALU, CMOS circuit design, SOI TFET simulation) could be an asset for hardware-accelerated AI or embedded AI systems.
Mentoring experience indicates leadership potential and ability to guide peers.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit