Note: The job is a remote job and is open to candidates in USA. SR2 is a Certified B Corporation™ focused on socially responsible recruitment, seeking an experienced Machine Learning Engineer to develop next-generation autonomous technologies. In this role, you will design, optimize, and deploy high-performance computer vision models for real-time applications on resource-constrained hardware.
Responsibilities
- Design, develop, and optimize computer vision models for real-time embedded applications
- Improve model performance using quantization, pruning, knowledge distillation, and other compression techniques
- Deploy machine learning models to embedded platforms such as ARM, NVIDIA Jetson, Qualcomm, and other edge AI hardware
- Develop clean, efficient, and maintainable software using Python and C++
- Build and optimize SLAM, object detection, tracking, feature extraction, and related computer vision algorithms
- Collaborate with multidisciplinary engineering teams to integrate machine learning into production systems
- Benchmark, profile, and optimize inference performance, balancing latency, accuracy, power consumption, and memory usage
- Stay at the forefront of machine learning research, applying emerging techniques to improve real-time performance on embedded devices
Skills
- Master's or PhD in Computer Science, Machine Learning, Electrical Engineering, or a related discipline
- 5+ years' experience in machine learning, deep learning, and computer vision
- Proven experience developing and deploying deep learning models in production environments
- Strong knowledge of TensorFlow, PyTorch, ONNX, TensorRT, and related machine learning frameworks
- Hands-on experience with model optimization techniques including quantization, pruning, and knowledge distillation
- Excellent Python and C++ programming skills with a focus on performance optimization
- Experience deploying models on embedded hardware such as NVIDIA Jetson, ARM platforms, Qualcomm AI accelerators, Raspberry Pi, or custom AI hardware
- A solid understanding of hardware-aware optimization techniques to maximize inference speed while minimizing resource usage
- Strong analytical and problem-solving skills with the ability to work independently and collaboratively
- Real-time SLAM, visual odometry, or multi-sensor fusion
- CUDA, OpenCL, or low-level hardware acceleration
- Robotics frameworks such as ROS
- Edge AI deployments across mobile, robotics, or IoT platforms
Benefits
- A collaborative, high-performing engineering culture.
- Comprehensive healthcare including medical, dental, vision, life, and disability insurance.
- Flexible annual leave and sick leave.
- Retirement savings support, FSA/HSA options, and commuter benefits.
- The opportunity to work on meaningful, technically challenging products using the latest AI and embedded technologies.
Company Overview