Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 2 days ago

Senior Machine Learning Engineer, Recommendation

Sekai7 open roles

Where
San Francisco, USA
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowSenior Machine Learning Engineer, RecommendationSekai · San Francisco, USA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Sekai's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 2 days ago

The posting

Sekai is building the TikTok for mini apps — an AI-driven consumer platform where people create, remix, share, and play interactive content instantly.

We are a Series A company backed by Khosla, a16z and Mayfield, with $30M raised to date. We are remote-first across all positions and are looking for ambitious, AI-native builders who want to help shape the next generation of consumer social products.

Download our app and give it a try!

- Android: https://play.google.com/store/apps/details?id=chat.sekai.app&hl=en_US

- iOS: https://apps.apple.com/us/app/sekai-create-remix-play/id6504506653

ABOUT THE ROLE

We are looking for a Senior Machine Learning Engineer to own search and recommendation systems for Sekai’s consumer product.

This role sits at the center of content discovery, user engagement, and content distribution. You will build the models and systems that decide what users see, what they search for, what they continue playing, and how high-quality content reaches the right audience.

This is a senior IC role for someone who has built real recommendation, search, ranking, or discovery systems in production for consumer apps, especially in entertainment-driven products.

WHAT YOU WILL OWN

- Build and improve recommendation and search systems across feed, discovery, search, and content continuation surfaces.

- Own retrieval and ranking systems, including candidate generation, embedding-based retrieval, two-tower models, ranking features, and online serving quality.

- Design, launch, and analyze recommendation/search experiments end-to-end, then use the data to iterate quickly.

- Improve recommendation quality for new users, new content, and fast-changing content pools.

- Build user, content, creator, and session-level representations from behavioral signals.

- Partner with product, data, and engineering teams to define metrics, run experiments, and ship measurable improvements to retention, engagement, and content distribution.

- Build practical ML systems that can move from prototype to production quickly, with clear monitoring and evaluation.

- Help shape the long-term ML architecture for AI-native content discovery.

WHAT WE ARE LOOKING FOR

- 5+ years of industry experience building production ML systems, with senior-level ownership of recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems.

- Hands-on experience building recommendation or search systems for consumer apps.

- Experience working on entertainment, social, gaming, short-form content, creator, or other engagement-driven consumer products.

- Strong practical experience with two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation.

- Strong product intuition around relevance, retention, engagement, satisfaction, cold start, and content distribution.

- Ability to translate messy user behavior into useful modeling signals and practical product improvements.

- Strong engineering fundamentals across modeling, data pipelines, backend integration, experimentation, and production ML systems.

- High ownership, fast execution, and clear communication in ambiguous product environments.

NICE TO HAVE

- Experience with AI recommendation, LLM-powered ranking, semantic search, personalized generation, or AI-native content understanding.

- Experience with UGC content ecosystems, creator marketplaces, or rapidly changing content catalogs.

- Experience with multimodal content understanding across text, image, video, interaction traces, or generated content.

- Experience with explore/exploit, contextual bandits, reinforcement learning, or long-term value optimization.

- Startup experience or experience building 0-to-1 ML systems with limited infrastructure.

BENEFITS

- Top compensation package, including competitive salary and meaningful equity.

- Comprehensive health insurance and benefits.

If you are excited about building at the frontier of AI, consumer social, and interactive entertainment, we would love to hear from you.

At Sekai, you will work with an AI-native team, move fast, own meaningful problems, and have the flexibility to explore new ideas from an early stage.

If you are excited about building at the frontier of AI, consumer social, and interactive entertainment, we would love to hear from you.

At Sekai, you will work with an AI-native team, move fast, own meaningful problems, and have the flexibility to explore new ideas from an early stage.

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Sekai's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on Sekai's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    Sekai's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.