Senior Machine Learning Engineer - Growth

Location: Remote within the United States; listed locations are Seattle and San Francisco

Salary: $171,063–$269,075 annual base pay across US geographic pay zones

Company

hirify.global develops software products that help teams collaborate and manage different types of work.

What you will do

• Design, build, and operate machine learning systems for personalized recommendations, engagement, activation, expansion, and sales experiences.
• Build reliable datasets, features, models, evaluation frameworks, and decisioning services across hirify.global's product portfolio.
• Develop unified, value-aware orchestration and ranking systems using user context, conversion probability, and expected lifetime value.
• Run offline policy evaluations and online experiments while monitoring attribution, latency, quality, fairness, and business outcomes.
• Define the evolution of ML capabilities and partner with product, engineering, data science, analytics, marketing, and sales teams.

Requirements

• 5+ years of related industry experience in machine learning.
• Bachelor's or Master's degree in Computer Science or equivalent experience.
• Expertise in Python and knowledge of Java, TypeScript, SQL, Spark, and cloud data environments such as AWS and Databricks.
• Experience building and scaling production machine learning models, datasets, and evaluation systems using large amounts of data.
• Ability to solve ambiguous and complex problems, communicate ML concepts to diverse audiences, and write performant production-quality code.
• Experience partnering with product, analytics, marketing, or sales teams on personalized customer journeys or sales-assist experiences.

Nice to have

• Experience with contextual bandits, uplift modeling, recommender systems, policy evaluation, causal inference, or decision optimization under uncertainty.
• Experience applying ML to growth, personalization, recommendations, ranking, experimentation, or decisioning.
• Experience in consumer or B2C SaaS, enterprise, or B2B environments.
• Understanding of engagement, activation, conversion, expansion, and retention metrics.

Culture & Benefits

• Flexible remote, office, or hybrid work arrangements.
• Health and wellbeing resources.
• Paid volunteer days and community support.
• Potential eligibility for benefits, bonuses, commissions, and equity.
• Recruitment accommodations and adjustments are available when needed.

Hiring process

• Identity verification may be required as a condition of employment.
• Recruitment accommodations can be requested at any stage of the process.