Machine Learning Engineer

Staff ML Engineer @ Go Offer

Go Offer is an AI-powered job search platform that helps professionals land jobs at top US companies — faster and smarter than doing it manually. We automate the hard parts: resume optimization, LinkedIn positioning, AI-driven applications at scale, recruiter outreach, and interview prep. Our clients are international professionals targeting the US job market, and our results speak for themselves.

We're a team of 70+ people growing fast, and we're building the AI infrastructure that powers everything under the hood.

What you'll work on

We're looking for a Staff ML Engineer to own the machine learning layer of our platform. This is a hands-on role — you'll be designing models, writing code, and shipping things that real users interact with every day.

Current problems on the table:

• Resume-to-job matching — building models that understand what makes a resume a strong fit for a specific role, beyond keyword overlap
• ATS optimization engine — understanding how applicant tracking systems score resumes and reverse-engineering that into actionable rewrites
• Recruiter outreach personalization — models that figure out the right message, the right person, and the right timing for cold outreach at scale
• Application volume intelligence — knowing which 500 jobs out of 10,000 are actually worth applying to for a specific candidate profile
• Interview signal extraction — pulling patterns from successful and unsuccessful interview outcomes to improve prep recommendations

This is not a research role. We move fast, we ship, and we measure everything by whether it helps candidates get more interviews and more offers.

What we're looking for

• You've built ML models that went into production and affected real users — not just notebooks and experiments
• Strong in Python — pandas, scikit-learn, and whatever else gets the job done
• You understand NLP and text modeling well enough to work with resume and job description data
• You can own a problem end-to-end — from defining what to measure, to building the model, to shipping it, to knowing if it worked
• You've worked in ambiguous environments where the problem wasn't handed to you pre-packaged
• Experience with LLMs and prompt engineering — we use Claude (Anthropic) and OpenAI heavily across the platform and expect our ML engineers to know how to work with and around them
• Comfortable working with small teams and without heavy process — we don't have six layers of approval, we have a problem and a deadline

Nice to have

• Experience in HR tech, recruiting, or career services — understanding the job search process from the inside helps
• Experience building ranking or recommendation systems
• Familiarity with ATS systems (Greenhouse, Lever, Workday, iCIMS) and how they parse and score resumes
• Experience working with unstructured text data at scale

What you get

• Equity in a fast-growing AI SaaS company
• Direct access to the founding team — no middlemen, no bureaucracy
• Hard problems that actually matter — we're not optimizing ad clicks, we're changing how people find jobs
• Remote-first with strong async culture
• Competitive compensation

Who we are

Go Offer has two products: a full-service Job Search Platform (resume, LinkedIn, AI applications, recruiter outreach, interview prep, offer negotiation) and an AI Career Bootcamp teaching 22+ AI tools through real internship projects. We've helped hundreds of international professionals land roles at US companies, and we're building the infrastructure to do it at 10x the scale.