Senior Machine Learning Engineer

Top Job
United States
26 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Machine Learning Recommender Systems Machine Learning Operations

Job description

  • Build recommendation and search across feed, discovery, search, and content continuation.
  • Own retrieval/ranking: candidate generation, embeddings, two-tower models, features, and serving quality.
  • Design, launch, and analyze recommendation/search experiments.

Bonus

  • Bonus signal: 5+ years production ML
  • Bonus signal: recommendation systems
  • Bonus signal: search ranking
  • Bonus signal: embedding retrieval

Anti-signals

  • Cannot show core Senior Machine Learning Engineer, Recommendation experience
  • Not comfortable with the listed work mode
  • Low ownership, coordination-only, or no shipped examples

Requirements

  • 5+ years industry experience building production ML systems with senior ownership.
  • Hands-on recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems.
  • Consumer apps, entertainment, social, gaming, creator, or engagement-driven products.
  • Two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation.

Benefits & conditions

  • Series A, $30M raised, backed by Khosla, a16z, Mayfield, and A*
  • Remote-first across all positions
  • Product sits at AI, consumer social, mobile, and interactive entertainment
  • Strong bias toward AI-native builders using modern AI tools deeply
  • Ownership-heavy startup environment: ship fast, learn from users, shape a new category early

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.indeed.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:50 min

Real life recommendation systems and final project conclusions

Lutske van der Meer Lutske van der Meer · WWC 2024

2:40 min

Understanding real-world recommendation systems in common platforms

Julian Joseph · LIVE

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

4:25 min

Optimizing agricultural practices through automated machine learning operations

Simi Olabisi · LIVE

2:19 min

Applying machine learning operations principles for robust automation

Simon Stiebellehner · WWC 2021

1:57 min

Evolution of machine learning algorithms and computing hardware

Alexandra Waldherr · LIVE

Videos

See all

Related articles

See all