Machine Learning Engineer (Robotics)

TL;DR

Machine Learning Engineer (Robotics): Building and optimizing deep learning models for autonomous navigation and decision-making systems with an accent on computer vision, dataset management, and model deployment. Focus on designing scalable training pipelines, optimizing inference performance, and integrating machine learning solutions into real-world autonomous vehicle applications.

Location: Must be based in Austin, TX. On-site role, no remote options available. Candidates must be authorized to work in the U.S.

Company

hirify.global is an autonomous vehicle and robotics technology company currently scaling its robotaxi operations.

What you will do

• Design and refine deep learning architectures to improve navigation, object perception, and intent prediction.
• Curate and manage large-scale datasets for high-quality training and performance evaluation.
• Develop and maintain end-to-end training workflows, including distributed training and automated monitoring.
• Optimize model efficiency for hardware deployment, focusing on inference speed and model compression.
• Research and implement cutting-edge machine learning techniques to solve complex autonomous system challenges.
• Collaborate with robotics and software teams to deploy models directly into autonomous vehicles and delivery robots.

Requirements

• Authorized to work in the U.S.
• Strong proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX.
• At least 3 years of experience in neural network development, data collection, and deployment.
• Working knowledge of C++ and SQL.
• Ability to interpret research papers and apply new concepts to practical engineering tasks.
• Strong background in computer vision, LLMs, or generative AI.

Nice to have

• Advanced degree in Computer Science, Machine Learning, or Robotics.
• Experience with deployment optimization tools such as TensorRT or Triton.
• Previous work in autonomous vehicles or robotics environments.
• Contributions to ML open-source projects or publications in top-tier ML conferences.

Culture & Benefits

• Focus on high-impact innovation in autonomous transportation technology.
• Opportunity to work on end-to-end robotics software from research to production.
• Collaboration with a multidisciplinary team of researchers and engineers.
• Access to advanced deep learning architectures and large-scale proprietary datasets.