Research Engineer

About the Role

Develop novel approaches to representation learning and reasoning under uncertainty. Build models that predict who professionals should meet from sparse, noisy signals.

Responsibilities

• Research and develop models for representation learning and probabilistic reasoning
• Design systems that infer intent from sparse, noisy, and incomplete data
• Build and evaluate models that power professional matching and recommendations
• Translate research ideas into production-grade ML systems
• Run experiments, simulations, and offline evaluations to validate approaches
• Collaborate closely with engineering and product teams to deploy models at scale
• Stay current with advances in ML, statistics, and applied AI research

Qualifications

• Strong background in machine learning, statistics, or quantitative research
• Experience developing and shipping production ML systems
• Familiarity with representation learning, probabilistic models, or inference techniques
• Strong programming skills and comfort working with real-world data
• Publications in venues such as NeurIPS, ICML, or KDD are a plus
• Ability to operate across research and engineering with minimal supervision

Benefits

• Competitive salary range ($120K–$300K)
• Remote-friendly role
• Opportunity to work on novel ML problems with real-world impact
• Direct influence on core product intelligence
• Visa sponsorship available