AI & ML Resume Review & Tailoring with KUSHAGRA GUPTA

What We Will Cover:

• Role Alignment: Structuring your profile for specific tracks (MLE, Applied AI, MLOps, LLM Engineering, or Research).
• Project Framing: Transforming basic descriptions into quantified bullet points (e.g., latency reduction, throughput, model metrics, cost savings, and business impact).
• Technical Stack Optimization: Highlighting modern frameworks, serving infra (vLLM, Triton), vector databases, and MLOps tools without tech-stack clutter.
• ATS & Recruiter Screening: Formatting hacks and keyword integration to ensure your resume passes automated filters and catches hiring managers' attention within 10 seconds.
• Github & Portfolio Quick-Scan: Verifying that your linked repos and publications reinforce your resume narrative.

What You Need to Bring (Pre-Call Requirements)

To make the most of our call, please share the following at least 24 hours in advance:

1. Your current resume (PDF or Google Doc link).
2. 1–3 target job descriptions (JDs) or company profiles you are aiming for.
3. Links to relevant GitHub repositories, Hugging Face spaces, or papers (optional, but encouraged).

Deliverables / What You’ll Walk Away With

• Annotated, line-by-line feedback on your existing resume.
• Rewritten bullet point examples for your core ML/AI projects.
• A clear list of ATS keywords tailored to your target job titles.
• Actionable 7-day revision roadmap.
• Full recording of the session (and shared notes doc).