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.