Founding ML Engineer - Recommender Systems & Graphs

Centralize; San Francisco, New York (CA, NY); Hybrid; USD 150,000 - 230,000; Full time

Benefits offered by this job

Fully covered medical, dental, and vis

401(k)

Parental leave

Unlimited PTO + company holidays

Quarterly offsites

Equipment stipend

Job summary

Centralize is hiring its first ML engineer to lead ML and Applied AI across a relationship graph for enterprise deals. You’ll own end-to-end systems, design a layered knowledge graph and recommender stack, and ship models within weeks. You’ll report to the co-founder/CTO and help grow the ML team as it forms around you.

The role emphasizes productionized ML, ranking, graph-based models, and publishing findings while aligning with business outcomes and customer success.

Qualifications

• Proven experience shipping ML systems in production.
• Expertise in recommender/graph-based models.
• Strong knowledge of embeddings, retrieval, ranking.
• Ability to ship end-to-end research to product.
• Excellent written and verbal communication.
• Product-minded with deadlines.

Responsibilities

• Set the research direction for Centralize's trust graph.
• Design and build the layered knowledge graph and the recommendation systems on top of it: embeddings, retrieval, ranking, and link prediction that improve with every deal, signal, and outcome.
• Build next best actions: learn from past deals and outcomes to recommend who a rep should reach out to, why, and how.
• Drive research in production. Take ideas from first experiment to shipped feature in front of customers, and measure the impact in real deals.
• Own system design and model selection: decide when a third-party model or API is the right call and when to build in-house, and build the data, evaluation, and inference foundation that keeps it fast and reliable at enterprise scale.
• Publish what we learn in white papers and technical write-ups, present the work at conferences, and bring the findings back into the product.
• Lead complicated, long-horizon projects across engineers, writing the plan, aligning the team, and keeping the work moving for months.
• Power agents that surface the right relationship, person, or next step before a rep has to ask.
• Help build out the ML team as we grow.

Skills

ML engineering

Recommender systems

Knowledge graphs

Embeddings

Retrieval systems

Ranking models

Graph-based models

Deep learning

Communication skills

Education

MS/PhD in quantitative field

Job description

Centralize is hiring its first ML engineer to lead ML and Applied AI across a relationship graph for enterprise deals. You’ll own end-to-end systems, design a layered knowledge graph and recommender stack, and ship models within weeks. You’ll report to the co-founder/CTO and help grow the ML team as it forms around you.

The role emphasizes productionized ML, ranking, graph-based models, and publishing findings while aligning with business outcomes and customer success.