Senior Machine Learning Engineer (Advertising Technology)

TL;DR

Senior Machine Learning Engineer (Advertising Technology): Building and operating large-scale batch and real-time ML systems that power pricing, inventory optimization, ranking, and trust & safety across the ad platform with an accent on machine learning, distributed systems, and MLOps. Focus on translating modeling ideas into reliable, observable, and scalable ML systems, while setting technical direction, raising engineering standards, and mentoring others.

Location: United States - California - San Jose

Salary: $199,000.00 to $318,500.00 in San Jose

Company

hirify.global brands power global travel for everyone, everywhere.

What you will do

• Collaborate with Software Engineers and ML Engineers/Scientists to design and build large-scale batch and real-time ML systems for advertising use cases
• Propose, lead, and deliver high-impact ML applications across pricing, inventory, content, and trust & safety, aligning technical decisions with business outcomes
• Own the end-to-end lifecycle of mid- to large-scale ML projects, from system design and model development through deployment and production operations
• Establish and promote ML engineering best practices, including model quality, MLOps, observability, and scalable system design
• Mentor junior engineers and support teams in integrating ML into existing production systems

Requirements

• 8+ years (BS) / 6+ years (MS) of industry experience building and deploying machine learning models in production
• Strong experience with distributed data processing and large-scale datasets (Spark preferred)
• Proven ability to design, deploy, and operate real-time or near–real-time ML systems end to end, including feature pipelines, model training and validation, scalable inference, monitoring, drift detection, and retraining
• Proficiency in Python with ML frameworks such as PyTorch or TensorFlow, and strong working knowledge of Scala or Java
• Deep expertise in end-to-end MLOps, including training and inference workflows, CI/CD for ML, model versioning, and automated retraining
• Experience operating cloud-native ML platforms and distributed systems (AWS, SageMaker, Kubernetes, Spark, Databricks) with reliability, scalability, and cost awareness

Nice to have

• Proven experience building and scaling production ML and AI systems, including LLMs, RAG pipelines, embeddings, and retrieval-based architectures
• Strong foundation in machine learning fundamentals, including supervised and unsupervised learning, feature engineering, model evaluation, bias/variance tradeoffs, and offline vs online metrics
• Hands-on experience designing, training, tuning, and deploying ranking, prediction, classification, recommendation, forecasting, or NLP models
• Background in ads, marketplaces, e-commerce, or travel platforms is a plus

Culture & Benefits

• Full benefits package, including travel perks, generous time-off, parental leave, a flexible work model and career development resources
• Wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership