We are looking for Senior Computer Vision / ML Engineer, you will develop and implement computer vision and machine learning algorithms that operate on large-scale real-world video data. The role combines algorithm development and software engineering, with approximately equal focus on building high-performing models and turning them into robust, production-quality solutions. You will work independently, take ownership of your tasks and outcomes, and collaborate closely with other R&D teams to integrate your algorithms into FarmSee's production systems.
What You'll Do:
Develop and implement computer vision and deep learning algorithms for detection, segmentation, tracking, and re-identification.
Research, prototype, evaluate, and improve machine learning approaches using real-world datasets.
Develop high-quality Python code for both algorithmic development and production environments.
Design experiments, evaluate model performance, analyze failures, and continuously improve algorithm accuracy and robustness.
Define and support data collection and annotation processes required for model development and validation.
Optimize models and inference pipelines for performance and scalability.
Collaborate with backend, infrastructure, QA, and other R&D teams to integrate algorithms into production systems.
Use modern AI-assisted development tools such as Codex, Claude Code, Cursor, or equivalent as an integral part of day-to-day development, debugging, testing, and code improvement.
Stay current with relevant developments in computer vision, deep learning, and AI-assisted software development.

Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field. At least 5 years of hands-on professional experience in Computer Vision, Machine Learning, and Deep Learning. Strong practical experience with image segmentation, multi-object tracking, and visual re-identification (metric learning), as well as ML for tabular data. Strong understanding of classical image processing and computer vision techniques. Strong Python programming skills. Strong experience with PyTorch or other major deep learning frameworks. Solid understanding of batching, caching, numerical precision, and memory optimization for model deployment. Ability to write clean, maintainable, production-quality Python code. Strong understanding of object-oriented programming, software design principles, design patterns, testing, and software development best practices. Proven ability to work independently with minimal supervision and take full ownership of assigned tasks and outcomes. Practical experience using modern AI coding tools such as Codex, Claude Code, Cursor, or equivalent. Strong analytical and problem-solving skills. Good communication and collaboration skills. Advantage: Experience optimizing deep learning models for inference. Experience with TensorRT. Experience with NVIDIA Triton Inference Server. Experience profiling and optimizing GPU-based workloads.