About the Position

Inkitt is building the Disney of the 21st Century, standing at the forefront of technology and entertainment. Leveraging AI and predictive algorithms, Inkitt discovers unknown stories and turns them into blockbuster hits, producing a new $1M ebook every 7 days and selling directly to consumers through its Inkitt Galatea app. Bestsellers are then translated onto the screen through Inkitt CandyJar, the #1 US-based microdrama platform with billions of episodes streamed to date. Inkitt has become the 11th most bestseller-generating publisher in the world, boasting a 40x higher hit-rate than traditional publishers. Backed by some of the top VC’s such as: Khosla, Kleiner Perkins, and NEA Ventures, our recent expansion into Ironblood, the first AI Native streaming platform for action and adventure, is only the beginning of our journey to becoming the next-gen entertainment powerhouse.

Responsibilities

Own recommendations and discovery across Inkitt, Galatea, CandyJar and Ironblood - every surface where we decide what to put in front of someone next, plus the roadmap, experiments and revenue attached.
Design the experiences the models feed: home and feeds, search, browse, taste capture at onboarding, personalised notifications and re-engagement, cross-app discovery.
Partner closely with Data Science, who own the models and signals, on what those models need to predict and how we judge whether they got better.
Design and run recommendation experiments at a high cadence; ramp them on your own judgement; report results honestly including the losses.
Build the impact case before you build the feature. Know the difference between an offline metric moving and revenue moving.
Hit the impact you predicted.

Requirements

5–12 years of professional experience. We measure years on the job, not years holding a “product manager” title. If you came to product from data science, analytics or engineering, that is an advantage here rather than a gap.
You have shipped a recommendation, ranking, search or personalisation system that real users felt - and you can explain what you changed, what moved, and how you knew it was causal.
You understand how these systems work underneath. Candidate generation and ranking, cold start, feedback loops, popularity bias, exploration versus exploitation. You can hold your own with the people training the models.
You can tell an offline win from a business win. Plenty of people have improved an NDCG. We care that you have moved reading time, conversion or renewal, and that you can show the experiment design behind it.
Numbers you produce yourself. Advanced SQL. You build the analysis rather than commissioning it.
Consumer product instinct - this is a reader-facing experience, not an internal tool.

Nice to Have

Content or entertainment recommendations (streaming, serialized fiction, short-form video, audio, games).
LLM-based ranking, embeddings or generative approaches to catalogue understanding.
Experience with a catalogue created in-house rather than uploaded by users.

We Offer

Competitive salary range of $170,000 - $210,000 a year.
401k plan, designed to help you save for the future.
Health benefits tailored to your needs, including medical, dental, and vision coverage.
Professional coaching for everyone.
Team-building events, including our annual Tulum trip.
Unlimited access to our Galatea app and CandyJarTV app.
Unlimited budget for self-development books.
Charity donation of your choice at your one year anniversary.
Free lunch in office everyday.
Class Pass membership for US based employee and gym access for Berlin employees.
Dog-friendly offices in Berlin and San Francisco.

About the Company

At Inkitt, we strive to build a company culture and provide employment opportunities based on diversity and inclusion. We believe every author should have an equal opportunity to succeed, as should our team members. As a growing team from 20+ countries, we welcome everyone to apply.

We look forward to hearing from you!

Senior Product Manager, Recommendations

Job description