Software Engineer (ML Infrastructure)

TL;DR

Software Engineer (ML Infrastructure): Designing and maintaining a petabyte-scale data and ML platform for robotic autonomy with an accent on scalable data processing pipelines and discovery capabilities. Focus on building natural language querying, optimizing vector databases, and integrating with large-scale annotation platforms.

Location: Remote (USA or Canada)

Salary: $155K – $190K

Company

hirify.global is reimagining city logistics using personable sidewalk robots to reduce street congestion and benefit local businesses.

What you will do

• Develop highly scalable data processing pipelines for curation, annotation, and ML feature extraction.
• Build data discovery and search features, including natural language querying.
• Maintain and evolve orchestration systems and data schemas such as unified data attributes and scenario tagging.
• Integrate with 3rd party annotation providers to efficiently review large-scale data pre-annotations.
• Collaborate with autonomy engineers to refine data classifications and improve platform documentation.

Requirements

• BS or MS in Computer Science with a focus on data engineering or machine learning.
• 3+ years of industry experience building large-volume data processing and annotation workflows.
• Proficiency in Python and SQL.
• Hands-on experience with LLMs, VLMs, embeddings, and vector databases.
• Experience with annotation tools such as CVAT, LabelBox, or LabelStudio.
• Must be based in the USA or Canada.

Nice to have

• Experience integrating cloud inference platforms for LLMs/VLMs (ChatGPT, Gemini, etc).
• Experience working with multi-modal data (Lidar, Camera).
• Background in robotics systems.
• Expertise in optimizing large-scale vector databases.

Culture & Benefits

• Remote-first work environment across multiple North American hubs.
• Compensation includes equity options.
• Collaborative and respectful team culture driven by tech industry veterans.
• Opportunity to solve real-world problems leveraging robotics and computer vision at scale.