Machine Learning Engineer 5 - Ads Signals & Targeting

For our client, we are seeking a Machine Learning Engineer 5 - Ads Signals & Targeting to join the team of a leader in the Hospitality & Recreation space.

This role will focus on building and deploying machine learning solutions that improve real-time advertising performance and audience targeting. You will partner closely with cross-functional teams to enhance ad relevance, optimize signal usage, and support a high-quality viewer experience. The position also calls for a strong technical foundation in large-scale data systems and production model deployment.

Location: Remote - US based candidates only, no visa sponsorship available

Compensation: $466,000 – $750,000 annually

Responsibilities

• Build and deploy machine learning models for real-time advertising systems
• Create targeting features to enhance audience engagement based on contextual data
• Collaborate with cross-functional teams to ensure effective model production
• Optimize ad serving systems to improve brand safety and viewer experience
• Drive continuous improvement of machine learning processes for better ad relevance

Qualifications

• 5-7 years of experience in machine learning model deployment for real-time ad systems
• Expertise in developing machine learning models for ad targeting and audience expansion
• Proven history in designing user and contextual signals for ad platforms
• Strong programming skills in Java, C++, Python, or Scala, particularly in multi-threading and memory management
• Experience working with big data tools like Spark for massive datasets

Benefits

• Comprehensive health plans including mental health support
• 401(k) retirement plan with employer matching
• Stock option program and flexible spending accounts
• Generous paid time off policies, with 35 days for full-time hourly staff
• Flexible time off for full-time salaried employees

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.