Director, Applied Machine Learning
Skills
- Proven experience building and deploying production ML models, especially ranking/recommendation systems.
- Strong foundation in learning-to-rank, embeddings, gradient boosting, and neural networks.
- Hands-on experience with LLM workflows: prompt engineering, fine-tuning, RAG, and evaluation.
- Solid software engineering skills and familiarity with modern data + ML stacks and MLOps practices.
- Ability to translate ML concepts into business-relevant metrics and communicate clearly with cross-functional partners.
Responsibilities
- Partner with Product, Marketing, Operations, and business stakeholders to identify high-value ML opportunities and translate them into measurable modeling objectives.
- Design, develop, and iterate ranking, filtering, and personalization systems across product surfaces, owning feature strategy and evaluation.
- Apply LLMs and hybrid ML techniques for semantic understanding, intent detection, content generation, and internal workflow automation.
- Manage, mentor, and grow an applied ML team, setting standards for modeling rigor, experimentation, and production-readiness.
- Collaborate with ML engineering and platform teams to ensure scalable deployment, monitoring, and reliability of models.
- Define and run offline and online experiments (A/B tests) to measure impact and drive continuous improvement.
Education
- Bachelor's degree in Computer Science, Engineering, or related field required.
- Advanced degree (Master's or PhD) in a relevant field preferred.
Benefits
- Competitive base salary within posted USD range and potential variable compensation.
- Comprehensive health benefits (medical, dental, vision) and retirement savings plan.
- Remote-first work environment with flexible time off and paid leave.
- Professional development and mentorship opportunities; supportive, inclusive culture.
- Potential equity or long-term incentive participation depending on role and level.
Average salary estimate
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