At a Glance
- Tasks: Lead the development of an AI-powered job matching engine to connect users with their ideal roles.
- Company: Join a fast-growing, profitable company revolutionising job searches with AI technology.
- Benefits: Enjoy remote work, competitive salary, equity options, and 38 days off annually.
- Other info: Collaborate with top talent from leading companies in a dynamic, mission-driven environment.
- Why this job: Shape the future of AI in HR tech while making a real impact on people's careers.
- Qualifications: 5+ years in product management with strong ML expertise and a hands-on approach.
The predicted salary is between 80000 - 110000 £ per year.
About JobHire.AI
JobHire.AI is building a vertical AI agent that automates job search for professionals. We help thousands of users land interviews by finding, tailoring, and applying to jobs on their behalf — at scale and with precision. We are profitable, growing fast, and now entering a phase of deep product refinement and organic growth through exceptional UX and perceived value.
Mission
JobHire.AI is a personal AI agent for continuous professional development and happiness at work.
About The Role
We are seeking a highly analytical and hands-on Senior Tech AI/ML Product Manager with deep expertise in Machine Learning and Artificial Intelligence and Product Management. You will define and build a best-in-class job discovery and matching engine that connects users with the most relevant roles for them, at scale. You will own the strategy, discovery, and delivery of AI-powered features, focusing on matching, ranking, and personalization systems. The ideal candidate is an entrepreneurial thinker with an engineering mindset, capable of building rapid prototypes, making decisive calls with imperfect data, and relentlessly driving measurable outcomes.
Key Responsibilities
- Strategy & Ownership: Define the vision, strategy, and roadmap for AI/ML product features (JobHunt Engine). Take full ownership of the product lifecycle from hypothesis to scaled impact, focusing on business results, not just model performance.
- ML Product Leadership: Translate business problems into ML hypotheses and solutions. Work side-by-side with ML engineers and data scientists to define data requirements, evaluation frameworks, model monitoring, and delivery processes.
- Hypothesis Validation & Experimentation: Design and execute rapid, pragmatic validation cycles. Formulate clear hypotheses, choose the right validation method, and make data-driven go/no-go decisions under uncertainty.
- Structured Problem Solving: Apply critical thinking to decompose complex, ambiguous problems. Cut through noise, prioritize what truly matters, and build simple, effective solutions first.
- Cross-Functional Execution: Collaborate closely with Engineering, Data Science, and business teams. Communicate complex ML concepts clearly and align stakeholders on goals, trade-offs, and progress.
Expected Outcomes
- First 3 Months: Establish baseline measurement of job supply coverage across the U.S. market, including companies listed in the NASDAQ-100. Increase the percentage of users who successfully find a job through the platform by 50%.
- First 6 Months: Expand job vacancy coverage in the U.S. market, achieving up to 80% coverage of NASDAQ-100 companies and increasing overall coverage by 30%. Ship a major upgrade to the resume enhancement feature.
- 12 Months: Further expand U.S. job vacancy coverage, achieving a 50% increase in coverage of NASDAQ-100 companies compared to the 6-month baseline. Double the matching success rate and improve the application-to-offer conversion rate by 50%.
Requirements
- Technical & ML Expertise: Strong understanding of ML/LLM fundamentals. Hands-on experience building and scaling AI-powered features. Practical knowledge of modern AI/ML concepts.
- Product Development: 5+ years of experience in a Product Manager role, preferably in a data-intensive or ML-driven domain. Proven ability to formulate and rigorously test product/ML hypotheses.
- Mindset & Approach: Entrepreneurial & Hands-on. Outcome-Oriented. Thrives in Ambiguity.
- Communication: Fluent English and Russian. Excellent ability to communicate with technical and non-technical stakeholders.
Our Ideal Candidate
- Thinks simultaneously about business metrics and model quality metrics.
- Has a super-engineer mindset coupled with an entrepreneurial, get things done approach.
- Takes responsibility for the end result, not just the AI model.
- Doesn’t fall in love with technology but stays focused on solving the problem.
- Their first reaction to an idea is Let’s go build and test it.
Hiring Process
- HR Introduction Call
- Team Interviews
- Product challenge
- Reference Check
Benefits
JobHire.AI is a mission-driven, fastest-growing, and profitable global company. Amazing opportunity to build Job Hunt Engine, shaping the future of AI HRtech, people’s careers and lives. Brilliant team of the strongest A players from McKinsey, Nexters, Gett, Glovo. Remote work - work/life balance. Competitive package ($100-150k + Equity). 38 days Off (vacation + local holidays) and sick leave.
Sr. Tech AI/ML Product Manager - Job Hunt Engine employer: JobHire.AI
Contact Detail:
JobHire.AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Sr. Tech AI/ML Product Manager - Job Hunt Engine
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A personal connection can often get you a foot in the door faster than any application.
✨Tip Number 2
Prepare for interviews by researching the company and its culture. Tailor your responses to show how your skills align with their mission. We want to see that you’re genuinely interested!
✨Tip Number 3
Practice makes perfect! Do mock interviews with friends or use online platforms. The more comfortable you are speaking about your experience, the better you'll perform when it counts.
✨Tip Number 4
Don’t forget to follow up after interviews! A simple thank-you email can keep you top of mind and show your enthusiasm for the role. Plus, it’s a great way to reiterate your fit for the position.
We think you need these skills to ace Sr. Tech AI/ML Product Manager - Job Hunt Engine
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the role. Highlight your experience in AI/ML product management and how it aligns with our mission at JobHire.AI. We want to see how you can contribute to building our job discovery engine!
Showcase Your Analytical Skills: Since we're looking for someone with a strong analytical mindset, include examples of how you've used data to drive decisions in past roles. Share specific metrics or outcomes that demonstrate your impact — we love numbers!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your experiences and avoid jargon unless it's relevant. We appreciate a well-structured application that gets straight to the point.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at JobHire.AI
✨Know Your AI/ML Stuff
Make sure you brush up on your machine learning fundamentals, especially around NLP and recommendation systems. Be ready to discuss how you've applied these concepts in previous roles, as this will show your hands-on experience and technical expertise.
✨Showcase Your Product Management Skills
Prepare examples of how you've defined product strategies and executed them successfully. Highlight your experience with A/B testing and hypothesis validation, as this is crucial for the role. Think about specific metrics you've improved in past projects.
✨Be Ready to Solve Problems
Expect to face some complex, ambiguous problems during the interview. Practice breaking down these problems into manageable parts and think through your structured approach to finding solutions. This will demonstrate your critical thinking skills.
✨Communicate Clearly
Since you'll be collaborating with both technical and non-technical teams, practice explaining complex ML concepts in simple terms. Being able to align stakeholders on goals and trade-offs is key, so show that you can bridge the gap between tech and business.