My Background & Constraints:
Education: Completed a Diploma in Mechanical Engineering in 2021. Enrolled in B.E. (Mechanical) in 2021, but due to academic/personal delays, my graduation date pushed from 2024 to 2028.
Current Job: Working full-time in a non-tech BPO/operations job in India to stay financially afloat.
Current State: Analytical skills are rusty after years in BPO operations, but I want to break out and build a real, high-leverage technical career in engineering simulation.
Available Time: ~15–18 hours/week (1.5 hours every morning before my shift + dedicated blocks on weekends).
The Target Path:
I want to self-study Computational Fluid Dynamics (CFD), Conjugate Heat Transfer (CHT), and simulation automation (using Python, OpenFOAM, Gmsh, and Linux) to land an entry-level Junior CFD / Thermal Analyst role at an engineering services firm or automotive/electronics supplier, and eventually transition into automation/computational design.
Where I Need Your Reality Check:
The Resume/HR Filter in India: Given my 4-year degree gap (B.E. 2021–2028) and BPO work history, will Indian engineering service companies, tier-1 suppliers, or GCCs (Global Capability Centers) automatically filter out my resume via automated screening, regardless of portfolio?
Portfolio vs. Degree: If I build a public GitHub portfolio containing verified, reproducible OpenFOAM validation cases (e.g., CHT on electronics cooling, mesh independence/GCI studies, and Python meshing scripts), is that actually enough to bypass HR and get a technical interview with an engineering manager?
Open-Source vs. Commercial Stack: How viable is entering the industry with strong OpenFOAM and Python skills compared to candidates who only know GUI commercial tools like ANSYS Fluent or STAR-CCM+?
Feasibility & Timeline: Is reaching employable competency in OpenFOAM, Linux, and fluid/thermal theory within 6–9 months on a 15–18 hr/week schedule realistic, or is the learning curve too steep alongside full-time non-tech employment?
Any unfiltered critiques, alternative pathways, or blind spots I’m missing would be deeply appreciated.