Machine Learning Researcher / ML-Ops Engineer

Machine Learning Researcher / ML-Ops Engineer

About Rivet

Rivet is an American company building integrated task systems — fusing hardened hardware with software, sensors, AI, and networking — for industrial workforces and defense personnel. We create capabilities that multiply the effectiveness of every individual and withstand the world’s toughest environments.

We serve the people who build, operate, maintain, and defend our way of life. From technicians and engineers to first responders and service members, they embody the hard work, ingenuity, and meritocratic values that drive Western prosperity. Yet too often they are forced to rely on outdated tools that fail under modern pressures. Rivet exists to reset that priority.

At Rivet, you’ll join a mission-driven team that fuses disciplines to deliver decisive outcomes where they matter most. Whether shaping our technology, strengthening our partnerships, or building our culture, every role here contributes to equipping the front lines with the modern systems they deserve.

Who Thrives Here

• People with a deep disdain for bureaucracy, empire building, groupthink, dogma, corporate babble, and wasted time
• Teammates who want to work exclusively alongside others at the top of their field
• Experienced, no-nonsense professionals who are execution-focused and deliver high-quality solutions above all else

Role Description

We are seeking a talented ML Research Engineer to advance our computer vision and sensor fusion capabilities. This role combines cutting-edge research with practical implementation of machine learning pipelines for imaging, pose estimation, and model optimization. The ideal candidate will have strong expertise in Python, deep learning frameworks, and experience deploying ML models in production environments. You\'ll explore new ideas, validate them against the state of the art and deliver working prototypes that influence our product and research direction.

Role Objectives

Role Requirements

Foundational Knowledge (preferred understanding)

Preferred Qualifications

#J-18808-Ljbffr