Senior Machine Learning Engineer

Overview

• Develop and optimize high-performance C++ software for real-time computer vision and tracking algorithms on edge devices.
• Collaborate with engineers to integrate machine learning models into production pipelines, enhancing system orchestration and data processing.
• Design multithreaded and parallel processing pipelines for synchronized data handling from networked camera systems.
• Implement and optimize GPU-accelerated components using CUDA kernels to improve throughput and reduce latency.
• Develop robust data structures and memory management strategies for handling extensive video and sensor metadata streams.
• Profile and optimize code using advanced tools to enhance CPU and GPU utilization.
• Contribute to system-level architecture decisions, ensuring efficient inter-process communication and resource allocation.
• Collaborate with simulation teams to deploy and evaluate algorithms in realistic scenarios, ensuring fault handling and performance monitoring.

Key Responsibilities & Duties

• Design and implement high-performance C++ software for real-time computer vision applications on edge devices.
• Collaborate with ML engineers to integrate models into production pipelines, optimizing pre/post-processing workflows.
• Develop multithreaded pipelines for synchronized data processing from networked camera systems.
• Optimize GPU-accelerated components using CUDA kernels to enhance inference and tracking performance.
• Design efficient data structures and memory management strategies for handling large-scale video and sensor data.
• Utilize profiling tools to identify bottlenecks and improve system performance.
• Contribute to architectural decisions for edge platform deployment and resource scheduling.
• Collaborate with teams to deploy algorithms in test scenarios, ensuring robust fault handling and monitoring.

Job Requirements

• Bachelor's degree in Computer Science, Engineering, or related field.
• 5+ years of experience in modern C++ development, including object-oriented and generic programming.
• Proficiency in multithreading and concurrency for robust system development.
• Experience with parallel processing frameworks for real-time applications.
• Strong knowledge of data structures, algorithms, and memory management optimization.
• Hands-on experience with CUDA and GPU programming frameworks.
• Familiarity with integrating ML inference engines into production systems.
• Expertise in Linux-based development, including build systems and cross-compilation.