Artificial Intelligence Engineer - LLM Models

Key Responsibilities :

- Lead design and implementation of complex CV pipelines (object detection, instance segmentation, industrial anomaly detection)

- Own major modules from concept to deployment ensuring low latency and high reliability

- Transition algorithms from Python/PyTorch to optimized C++ edge GPU implementations using TensorRT, ONNX, and GStreamer

- Collaborate with cross-functional teams to refine technical strategies and roadmaps

- Drive long-term data and model strategies (synthetic data generation, validation frameworks)

- Mentor engineers and maintain high engineering standards

Required Skills & Qualifications :

- 310 years of experience in architecting and deploying CV systems

- Expertise in multi-object tracking, object detection, semi/unsupervised learning

- Proficiency in Python, PyTorch/TensorFlow, Modern C++, CUDA

- Experience with real-time, low-latency model deployment on edge devices

- Strong systems-level design thinking across ML lifecycles

- Familiarity with MLOps (CI/CD for models, versioning, experiment tracking)

- Bachelors/Masters degree in CS, EE, or related fields with strong ML and algorithmic foundations

- (Preferred) Experience with NVIDIA DeepStream, GStreamer, LLMs/VLMs, open-source contributions