Senior Product Manager (12 Month Contract)

Most PM roles ask you to ship features. This one asks you to build something smarter.

We're looking for a Senior PM to own the intelligence layer of our learning platform: the systems that decide what surfaces, when, for whom, and why. Search relevance. Personalized recommendations. Agentic discovery workflows that don't just respond to users, but actively help them move forward. If you've ever watched a recommendation engine quietly get better over weeks of real user behaviour and found that more satisfying than any launch announcement, this role was built for you.

Why you'll love this role:

This is a 12-month contract with genuine scope and real ownership. You won't be inheriting a polished system; you'll be shaping one that has serious room to get smarter.

• You'll work at the intersection of ML, UX, and data, not just on top of it
• You'll have the autonomy to design experiments, make calls, and drive direction without waiting on approvals
• You'll partner with a cross-functional team across engineering, data science, design, content, and GTM that's invested in getting this right
• You'll see the direct impact of your work in user behaviour, model performance, and platform intelligence over time

What you'll own:

You'll lead product across search, recommendations, content intelligence, and agentic discovery. That means shaping how the platform understands content, models user preferences, and surfaces the right learning at the right moment, across standalone, embedded, and API-based experiences.

The systems under your remit:

• High-intent search — improving relevance, ranking logic, and retrieval quality
• Personalized recommendations — evolving ML models and designing feedback loops that compound over time
• Intelligent filtering & categorization — making it easier for users to navigate a growing content library
• Content metadata enrichment — strengthening accuracy and coverage so the system understands what it's working with
• Preference & behavioural modelling — building personalization logic based on role, industry, region, and real usage signals
• Agentic discovery & curation workflows — designing systems that don't just respond to users, but proactively help them move forward
• Experimentation frameworks — building the scaffolding that lets the team test, measure, and iterate quickly
• Explainability — designing AI-driven experiences users can understand and trust

What you'll spend your day doing:

• Breaking down complex, ambiguous problems into small, high-impact releases that ship quickly and generate real signal
• Working closely with data scientists to understand model trade-offs, experiment design, and ranking logic
• Partnering with engineering to evolve traditional ML recommendation models and experiment with modern AI techniques
• Collaborating with design, content, and GTM teams to keep momentum high and decisions clear
• Surfacing trade-offs early and making calls with imperfect information, without getting stuck in analysis paralysis
• Running experiments, reading behavioural data, and iterating based on what you find rather than what you assumed
• Thinking commercially about how discovery quality flows through to activation, engagement, retention, and partner value

About you: 

Your background:

• 5+ years of product management experience, with meaningful time on ML-powered or data-heavy products
• You've owned search, personalization, recommendations, marketplace discovery, or content ranking before, not just observed it from a distance (must have)
• Experience in B2B SaaS, HR tech, content platforms, or compliance is a plus, but not a dealbreaker

How you think:

• You think in systems, not features. Feedback loops, signal quality, and long-term defensibility matter more to you than UI polish
• You're AI-fluent. You understand the difference between traditional ML and LLM-based approaches, and you know how to design responsibly with probabilistic systems and agentic behaviour
• You think commercially. You connect the dots between discovery quality and real business outcomes

How you work:

• You're data-comfortable. You can sit with engineers and data scientists, understand what they're building, and make informed calls about trade-offs
• You have a bias to action. You ship, measure, and iterate; you don't wait for perfect certainty
• You have grit. Ambiguous problem spaces don't stall you; you like building while learning
• You're a clear communicator. You surface trade-offs, make decisions legible, and help teams move without getting stuck

Join our team at Go1 and be at the forefront of transforming education through innovative learning solutions. Together, we can change the world. One learner at time. 

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