Computer Vision / Machine Learning Software Engineer

TL;DR

Computer Vision / Machine Learning Software Engineer (Computer Vision/ML): Build compute-constrained models for deployed robots, using large-scale sensor data to improve environmental awareness and deliver deeper inventory insights with an accent on 2D/3D computer vision and performance optimization for training and inference. Focus on optimizing model accuracy/speed under compute constraints, improving ML pipelines for dataset management and deployment, and collaborating to ship CV/ML models into production.

Location: Mountain View, CA (Hybrid)

Company

hirify.global builds autonomous drones that use computer vision and robotics to automatically track warehouse inventory.

What you will do

• Develop solutions for advanced computer vision tasks.
• Optimize performance, accuracy, and speed of compute-constrained models.
• Collaborate across teams to deploy CV/ML models into production.
• Improve ML pipelines and infrastructure for dataset management, training, and deployment.
• Spend ~20% of time on R&D to experiment with state-of-the-art techniques.
• Drive business value by applying work across robotics, software, and deployment teams.

Requirements

• 5+ years of industry experience in Computer Vision / Machine Learning with Python and PyTorch.
• Expertise in 2D and 3D computer vision techniques.
• Proficiency with Linux, Git, AWS/GCP, and CI/CD workflows.
• Experience in performance engineering for deep neural networks (training and inference).
• Knowledge of model optimization for embedded systems, including knowledge distillation, model quantization, and network pruning.
• In-person hybrid role in Mountain View, CA; US work authorization is preferred but not required (visa sponsorship available).

Nice to have

• Experience with C/C++.
• Familiarity with ROS (Robot Operating System).
• Knowledge of model deployment frameworks (TensorRT, RKNN, OpenVINO, ONNX, CoreML).
• Experience with TypeScript/JavaScript and Django.
• Experience with data labelers, tooling, and data management.

Culture & Benefits

• In-person hybrid work in Mountain View, CA.
• Visa sponsorship available if needed.
• 20% of time allocated to R&D and experimentation with new techniques.
• Fast-paced startup environment with room to take ownership.
• Focus on continuous learning and exploring new technologies to advance ML capabilities.