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.
The problem you’d own
Inkitt has more story than anyone can read. Galatea, CandyJar and Ironblood each depend on putting the right story in front of the right person at the right moment — and the quality of that match drives reading time, subscription conversion and renewal across all three apps.
We have a strong Data Science team, and they own the underlying signals and models. You own what users actually experience. Recommendations and discovery across every surface we have: home and feeds, search, browse, onboarding taste capture, notifications and re-engagement, and the cross-app connections between our four products. You decide what we put in front of someone next, everywhere we put anything in front of them — and you are accountable for the reading time, conversion and revenue that comes out of it.
How We Work — please read this part carefully
Ali, our founder and CEO, sets company priorities. You own the ideas. You will spend part of every day researching competitors, the industry and our users to generate new feature ideas, and you will keep a live Top 3 list of the highest-impact ideas for your area — a new idea only enters by beating one already on it.
You pitch on a single slide with a rough impact calculation attached. Ali rejects the ones that will not move the number enough to justify building them. That happens often, to everyone. The loop is pitch, get rejected, sharpen, re-pitch — continuously, alongside delivery.
Once approved, you own execution outright, including release and A/B ramping. Four weeks after launch, every feature is reviewed against the impact you predicted before you built it. Your performance is measured on two things: how often you beat your own Top 3, and the realised impact of what you ship.
What You’ll Do:
- 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
What You'll Bring:
- 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.
- Based in San Francisco. This role is five days a week onsite.
- 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.
Who We Are Looking For:
- Generates ideas rather than waiting for them
- Brings solutions instead of problems
- Data driven — and does the analysis themselves
- Quick to action
- Comfortable being measured against their own forecast
- Looking for exponential career growth
- Have lots of fun building a generational AI x Entertainment company
What We’ll Offer:
- 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
Skills Required
- 5–12 years of professional experience, including relevant experience in data science, analytics, engineering, or product management
- Shipped a recommendation, ranking, search, or personalization system used by real users
- Ability to explain causal experiment design and resulting business impact
- Understanding of candidate generation, ranking, cold start, feedback loops, popularity bias, and exploration versus exploitation
- Advanced SQL and ability to independently perform analysis
- Consumer product judgment and experience building reader-facing experiences
- Based in San Francisco and able to work onsite five days per week
- Experience with content or entertainment recommendations
- Experience with LLM-based ranking, embeddings, or generative catalog understanding
- Experience with internally created content catalogs
What We Do
Inkitt is a pioneer at the forefront of Data Driven Publishing. Using an analytic and objective approach, we’ve discovered hundreds of talented authors around the world with over 50% of our published authors achieving $100,000+ in sales. We have forever changed the traditional publishing model by inventing an algorithm which analyzes users' reading behavior to identify hits, in turn removing subjectivity from the equation. This gives Inkitt the unique ability to discover hidden talents that might otherwise have gone unnoticed.
Why Work With Us
We are on a mission to discover hidden talents and turn them into globally successful authors. 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.
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