Machine Learning Infrastructure Engineer

ob Title: Machine Learning Infrastructure Engineer Computer Vision & AI

Location: Redwood City, CA (Hybrid Onsite 3 days/week)
Job Type: Contract-to-Hire or Full-Time
Pay Rate (Contract): $80 $90/hr (up to $100/hr for C2C)
Salary (Full-Time): $165K $210K

About the Role

We are seeking a highly skilled Machine Learning Infrastructure Engineer to join a cutting-edge AI team focused on real-time video analytics and computer vision. This role is ideal for someone passionate about building scalable ML systems and integrating the latest advancements in AI, including LLMs, LVMs, and Retrieval-Augmented Generation (RAG).

Key Responsibilities

• Design and build robust machine learning infrastructure to support deep learning models on large-scale video data.
• Develop scalable data engines for collecting, managing, and labeling training data.
• Collaborate with research scientists to integrate state-of-the-art AI models into production systems.
• Optimize infrastructure for continuous training, evaluation, and deployment of computer vision models.
• Stay current with the latest trends in AI, ML, and computer vision to drive innovation.

Required Qualifications

• 6+ years of industry experience (minimum 4 years in the U.S.)
• BS/MS in Computer Science or related field
• Strong foundation in machine learning, deep learning, and computer vision
• Proven experience with scalable ML infrastructure and distributed systems
• Proficient in Python and software development best practices
• Experience with LLMs, LVMs, and RAG in production environments
• Excellent communication and collaboration skills

Nice to Have

• Experience working in real-time video processing environments
• Familiarity with cloud-based ML platforms and MLOps tools

Interview Process

• Initial phone/video screen
• Onsite interview (includes technical deep dive and team fit)