Senior Product Manager, Recommendations

About the role

Inkitt is building the Disney of the 21st Century, leveraging AI and predictive algorithms to discover unknown stories and turn them into blockbuster hits. The company produces a new $1 M ebook every 7 days and distributes it through the Inkitt Galatea app, while best‑sellers are adapted for screen via Inkitt CandyJar, the #1 US‑based micro‑drama platform. Inkitt’s recent expansion into Ironblood, an AI‑native streaming platform for action and adventure, continues its mission to become a next‑gen entertainment powerhouse.

The problem you’ll own is matching the right story to the right person at the right moment across Inkitt, Galatea, CandyJar and Ironblood. Recommendations and discovery appear in home feeds, search, browse, onboarding taste capture, notifications, re‑engagement, and cross‑app connections. You will decide what each user sees next and be accountable for the resulting reading time, conversion and revenue.

Ali, the founder and CEO, sets company priorities. You will spend part of every day researching competitors, the industry and users to generate new feature ideas, maintain a live “Top 3” list of highest‑impact ideas, pitch them on a single slide with rough impact calculations, and iterate based on feedback. Once an idea is approved you own execution, release, A/B ramping, and post‑launch impact analysis.

Responsibilities

• Own recommendations and discovery across Inkitt, Galatea, CandyJar and Ironblood—including roadmap, experiments and revenue impact.
• Design the experiences the models feed: home and feeds, search, browse, onboarding taste capture, personalised notifications, re‑engagement, and cross‑app discovery.
• Partner closely with Data Science on model signals, prediction requirements and evaluation criteria.
• Design and run recommendation experiments at a high cadence; ramp them based on judgement; report results honestly, including any losses.
• Build the impact case before building a feature, distinguishing offline metric movement from revenue movement.
• Deliver the impact you predicted and continuously beat your own “Top 3” ideas.

Qualifications

• 5–12 years of professional experience (measured by years on the job, not by title).
• Background in product, data science, analytics or engineering is a strong advantage.
• Successfully shipped a recommendation, ranking, search or personalisation system used by real users, and can explain the changes, impact and causal evidence.
• Deep understanding of candidate generation, ranking, cold‑start, feedback loops, popularity bias, and exploration vs. exploitation.
• Ability to discuss technical details with model‑training teams and differentiate offline wins from business wins.
• Proven track record of moving reading time, conversion or renewal, backed by rigorous experiment design.
• Advanced SQL skills and a habit of building your own analysis rather than commissioning it.
• Consumer‑product instinct for a reader‑facing experience.
• Based in San Francisco and able to work onsite five days a week.
• Nice to have: experience with content or entertainment recommendations (streaming, serialized fiction, short‑form video, audio, games); LLM‑based ranking, embeddings or generative approaches; experience with an in‑house catalogue rather than user‑uploaded content.

Benefits

• 401(k) plan designed to help you save for the future.
• Comprehensive health benefits, including medical, dental, and vision coverage.
• Professional coaching for every employee.
• Team‑building events, including an annual trip to Tulum.
• Unlimited access to the Galatea app and CandyJar TV app.
• Unlimited budget for self‑development books.
• Charity donation of your choice at the one‑year anniversary.
• Free lunch in the office every day.
• ClassPass membership for US‑based employees and gym access for Berlin employees.
• Dog‑friendly offices in Berlin and San Francisco.
• Commitment to diversity, inclusion and equal opportunity.

Schedule

Based in San Francisco. This role is onsite five days a week.