Senior Research Engineer (AI)

TL;DR

Senior Research Engineer (AI): Building and improving production-grade recommendation systems for U.S. commerce with an accent on machine learning fundamentals and AI-augmented workflows. Focus on designing scalable, fault-tolerant systems, leveraging internet-scale datasets, and owning the full lifecycle of ML models in production.

Location: US-based, hybrid flexibility (occasional in-person events/sessions required)

Company

hirify.global is a global technology company providing iconic digital products and omnichannel advertising solutions to hundreds of millions of users.

What you will do

• Lead the design and implementation of complex research engineering systems and machine learning models.
• Integrate AI tools to accelerate development, including rapid prototyping, automated testing, and code refactoring.
• Take end-to-end ownership of systems and models, ensuring observability and robust CI/CD pipelines.
• Collaborate with Product Managers and Architects to translate business requirements into technical roadmaps.
• Mentor junior and mid-level engineers through design reviews and code feedback.
• Develop and maintain production-grade services that process massive data volumes with low-latency requirements.

Requirements

• 5+ years of professional experience in software engineering, machine learning, or AI.
• B.S. or M.S. in Computer Science or equivalent.
• Strong proficiency in Python (Java or Scala acceptable).
• Demonstrated experience designing, building, and maintaining production-grade ML systems in distributed environments.
• Fluent in spoken and written English.
• Experience using AI-assisted coding tools.

Nice to have

• Expertise in building and maintaining LLMs in production.
• Experience with big data technologies such as Hadoop, Spark, HBase, or Storm.
• Strong background in cloud platforms like AWS or GCP.
• Deep understanding of observability and proactive system health management.

Culture & Benefits

• High degree of flexibility regarding work location and hybrid schedules.
• Opportunities to work with internet-scale datasets on high-impact products.
• Focus on modern development environments and Agile methodologies.
• Collaborative team environment with an emphasis on mentorship and technical excellence.
• Equal opportunity employer committed to accessibility and inclusivity.