Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Building and optimizing large-scale machine learning pipelines for a cloud-native consumer data platform with an accent on model deployment, performance monitoring, and scalability. Focus on integrating ML solutions into production environments, refining data feature engineering, and operationalizing research models within the hirify.global ecosystem.

Location: USA-based with flexible hybrid work options (occasional in-person events required)

Salary: $128,250–$266,875/year

Company

hirify.global is a global technology company providing digital platforms for content, search, and advertising for hundreds of millions of users.

What you will do

• Develop and optimize end-to-end machine learning solutions to solve complex business problems at scale.
• Build and maintain reliable production pipelines for training, evaluating, and deploying ML models.
• Implement monitoring frameworks to track model performance, latency, and data quality in real-time.
• Design robust features using large-scale data processing frameworks like Spark or Beam.
• Collaborate with data scientists to transition research-based models into scalable production services.
• Provide technical documentation and share knowledge with the wider engineering organization.

Requirements

• BS or MS in Computer Science, Data Science, or equivalent practical experience.
• 5+ years of software engineering experience, including at least 3 years dedicated to machine learning engineering.
• 2+ years of hands-on experience in implementing and deploying production ML models.
• Strong proficiency in Python or Java with experience in ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Experience with cloud ecosystems such as GCP (BigQuery, Dataflow) or AWS.
• Proven ability to translate business requirements into technical ML implementations.

Culture & Benefits

• Comprehensive benefits including healthcare and 401(k) plans.
• Flexible hybrid work environment focused on productivity and employee work-life balance.
• Access to professional development and education stipends.
• Inclusion initiatives supported by 11 diverse employee resource groups.
• Work environment that emphasizes innovation, reliability, and technical impact.