Senior Research Scientist (Monetization)

TL;DR

Senior Research Scientist (ML/Monetization): Leading the algorithmic design of advanced models for ranking, personalization, and revenue optimization for hirify.global Mail with an accent on large-scale machine learning and causal inference. Focus on designing state-of-the-art deep learning architectures to drive measurable business impact through ads targeting and dynamic pricing.

Location: United States of America (Hybrid)

Salary: $128,250 - $266,875 per year

Company

hirify.global is a global media and technology company providing a wide range of digital services, including the high-scale hirify.global Mail platform.

What you will do

• Lead research and algorithmic design for ranking, personalization, recommendation systems, and revenue forecasting.
• Design, train, and evaluate SOTA machine learning, deep learning, and reinforcement learning models.
• Incorporate LLM-driven synthesis into monetization models to prototype hybrid architectures.
• Collaborate with engineering partners to transition machine learning prototypes into production.
• Mentor and conduct technical assessments for senior and mid-level research scientists and ML engineers.
• Stay current with research trends and contribute via publications, patents, or technical presentations.

Requirements

• PhD (preferred) or Master’s degree in Computer Science, Statistics, Applied Mathematics, or a related field.
• 8+ years of industry experience (or 5+ years with a PhD) in ML, deep learning, or related fields.
• Proven expertise in optimizing business metrics such as CTR, CVR, and eCPM.
• Proficiency in Python and frameworks like TensorFlow, PyTorch, Hugging Face, Pandas, and NumPy.
• Experience leveraging AI-assisted development tools to accelerate research iteration.
• Must be based in the United States of America.

Nice to have

• Familiarity with Reinforcement Learning and online decision systems.
• Experience building and fine-tuning LLMs for search, retrieval, or monetization tasks.
• Hands-on experience with GCP, AWS, Hadoop, or Spark.
• Contributions to the ML research community through peer-reviewed publications or Kaggle.
• Strong understanding of causal inference and A/B testing at scale.

Culture & Benefits

• Flexible hybrid work options with occasional in-person events.
• Comprehensive benefits package including healthcare and 401k.
• Support for professional growth with education stipends.
• Inclusive environment with 11 employee resource groups (ERGs).
• Practical perks such as backup childcare.