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Machine Learning Engineer, Marketplace

San Francisco

SpringCube

Full-time - Senior Engineer

IT Services & Consulting

Posted 2 weeks ago

Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview

A rapidly growing AI infrastructure company is building the foundation that connects human expertise with frontier AI models. The organization enables millions of domain experts to contribute to AI development through large-scale training and evaluation systems while helping enterprises capture and operationalize institutional knowledge. With a strong presence in the AI ecosystem, the company works alongside researchers, operators, and leading AI organizations to shape the future of intelligent systems and the evolving AI economy.

The organization is seeking a Machine Learning Engineer, Marketplace to build the models and decision systems that power its hiring and talent marketplace engine. This role focuses on developing search, ranking, recommendation, personalization, and candidate-job matching systems that directly influence product performance and business outcomes.

The successful candidate will work on large-scale applied machine learning challenges involving sparse and delayed feedback, cold-start problems, noisy signals, and marketplace optimization. This position offers the opportunity to build production-grade ML systems that balance quality, speed, conversion, and marketplace efficiency across a rapidly expanding global talent network.

Key Responsibilities

  • Develop ranking and matching systems that determine which candidates and opportunities are surfaced across the platform.
  • Build recommendation, personalization, and marketplace optimization models.
  • Design and maintain retrieval, scoring, and decision-making pipelines operating at global scale.
  • Create feedback loops that learn from downstream hiring outcomes rather than solely engagement metrics.
  • Develop real-time and batch inference systems embedded within mission-critical product workflows.
  • Improve candidate-job matching using embeddings, structured data, and behavioral signals.
  • Optimize ranking systems for long-term hiring outcomes despite delayed and incomplete labels.
  • Design models that balance marketplace objectives such as fill rate, quality, speed, and conversion.
  • Build systems for candidate allocation, opportunity routing, and marketplace liquidity optimization.
  • Develop evaluation frameworks and experimentation methodologies that connect model performance to business results.

Required Qualifications

  • Proven track record of deploying machine learning systems into production environments.
  • Experience with ranking, recommendation, search, matching, or marketplace-focused machine learning problems.
  • Strong understanding of model design, objective functions, evaluation methodologies, and trade-off analysis.
  • Ability to work across the full applied machine learning stack, including data pipelines, feature engineering, model training, inference, and iteration.
  • Strong software engineering fundamentals with a focus on building simple, scalable, and reliable systems.
  • Experience solving complex optimization challenges within large-scale platforms or marketplace environments is highly desirable.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

  1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
  2. No Client Relationship: This company is not a client of SpringCube unless stated.
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