What are the responsibilities and job description for the Brand Ads Machine Learning Engineer position at HireIO, Inc.?
- Company Overview**
- Job Description**
- Key Responsibilities**
- Lead the development of advanced forecasting models that enable advertisers to optimize ad spend and maximize ROI
- Build innovative monetization products that enhance user engagement and boost revenue generation for brands
- Work on scalable, high-performance ads systems, focusing on ads bidding, ranking, and content delivery
- Collaborate on building ML-powered algorithms for ad personalization, recommendation systems, and ranking mechanisms
- Leverage NLP and Computer Vision (CV) technologies to enhance content understanding and improve ad targeting
- Contribute to the continuous evolution of TikTok's ad tech stack, driving system reliability, scalability, and performance in a globally distributed environment
- Partner closely with global engineering and product teams to drive impactful solutions at scale
- Qualifications & Skills**
Minimum Qualifications:
- Strong proficiency in programming languages like Go, C/C , Python (or other general-purpose languages)
- Proven ability to solve problems in a structured and efficient manner, with a critical thinking approach to system design
- Experience with ads technologies (brand ads, auction systems, bidding, ranking, and forecasting) or similar domains
- Hands-on experience with Machine Learning, including but not limited to forecasting, Deep Learning, NLP, ranking systems, or recommendation systems
- Background in working with large-scale systems, data science, or backend engineering
- A proven track record of contributing to and maintaining high-availability, high-performance systems
- BS/MS in Computer Science, Computer Engineering, or a related field, with 5 years of relevant experience
- Extensive experience with machine learning frameworks and techniques, including data mining, deep learning, and data analysis
- Strong sense of product design, with experience translating business needs into technical solutions and implementing successful features
- Familiarity with cloud technologies (AWS, GCP, etc.) and distributed systems is a plus