Case Study 9: How Scale.jobs Helped Secure Candidate Get an Offers at AWS

How an intern-level candidate used a structured, personalised strategy to land at Amazon Web Services, with the luxury of choosing between offers.

The challenge

Breaking into ML and SDE as an intern, without a professional track record to lean on.

Harshit came in at the start of his career, targeting three distinct tracks: ML Research internships, ML NLP internships, and SDE roles. Without professional experience to back his profile, the application strategy had to work harder. Generic outreach wouldn't cut it. What he needed was a personalised approach, one built specifically for internship-level candidates competing at companies that ordinarily see thousands of applicants per opening.

The insight

A structured strategy turns an intern profile into a competitive one.

The difference between an intern who lands interviews and one who doesn't often isn't the profile, it's the targeting. scale.jobs designed a strategy specifically scoped to internship roles at relevant companies and industries. 329 targeted applications produced a steady stream of interview calls, and within weeks Harshit had something most candidates never experience: real options. Multiple offers, each earned, each legitimate.

The journey

1. Onboarding & personalised strategy: Three target tracks were defined: ML Intern Research, ML Intern NLP, and SDE. A personalised application strategy was built for each, scoped to companies and industries where Harshit's academic profile would resonate.
2. 329 targeted applications: Applications went out with consistent quality across all three tracks. Harshit focused entirely on interview prep — scale.jobs handled every submission. A steady stream of callbacks followed within weeks.
3. Six interview calls, multiple offers: Strong traction across all three tracks put Harshit in an enviable position: choosing between multiple internship offers rather than chasing any single one. That's a different kind of problem — a good one.
4. Placed at Amazon Web Services: From the options in front of him, Harshit accepted the role that best aligned with his long-term goals — an internship at AWS. Not a default, not a fallback. A deliberate choice made from a position of strength.

scale.jobs built a strategy tailored specifically for my internship goals. Interview calls started coming in steadily, and I found myself choosing between multiple offers, something I didn't expect at this stage. I chose AWS, and I couldn't be more excited about where this first step is taking me. — Harshit, placed at Amazon Web Services

Key takeaways

1. Intern-level doesn't mean generic strategy: Harshit's search was built specifically for internship roles, not adapted from a template designed for mid-level professionals. The right strategy for your stage looks different from the right strategy for someone else's
2. Multiple tracks, one coordinated effort: Three different role types, ML Research, NLP, SDE, were pursued in parallel without Harshit having to manage them separately. Coordination across tracks is where opportunities get missed when you're doing it alone.
3. The best first step is a chosen one: Harshit didn't take the first offer that came in. He chose AWS from a genuine set of options. That kind of deliberate first step sets a different trajectory than accepting whatever arrives first out of urgency.
4. scale.jobs does the grind, you do the interviews: 329 applications submitted without Harshit spending a single hour on submissions. Every hour he saved went into interview preparation, exactly where it should have gone.

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