Role Purpose
Develops and implements AI solutions, with strong experience in Computer Vision especially on NVIDIA GPU-based systems. This role is responsible for analyzing problems, designing appropriate AI approaches, and ensuring models are effectively implemented and deployed in production environments.
Job Description
- Translate business and technical problems into structured AI problem definitions with clear modeling strategies.
- Collaborate with PMs, BSAs, and the AI Engineering team to ensure AI solutions are technically feasible, aligned with business goals, and realistic within project constraints.
- Develop and implement AI solutions with strong depth in Computer Vision, while remaining adaptable across predictive modeling, classification, and LLM based systems.
- Determine the appropriate AI approach, model architecture, and optimization strategy based on data characteristics and system constraints.
- Design and optimize AI models to effectively leverage some edge computing with AI accelerator devices, especially on NVIDIA accelerator for both training and inference workloads.
- Identify potential risks, model limitations, and edge cases to ensure AI solutions remain scalable, maintainable, and reliable in production environments.
- Evaluate model performance, trade-offs, and computational efficiency, particularly in GPU-based environments.
- Ensure lon-term maintainability of AI solutions by considering model lifecycle, monitoring, and performance sustainability.
- Provide technical guidance in experimentation, model validation, and system integration to maintain solution quality and consistency.
Job Requirements
- Possess a Bachelor, Diploma 3, or Diploma 4 degree from IT, Computer Science or other related majors.
- Have a minimum 2-3 years of experience in AI / Machine Learning development, preferably with strong exposure to Computer Vision systems.
- Proven ownership in delivering AI solutions from experimentation to production integration.
- Strong analytical capability in model and method selection based on problem needs.
- Proficiency in Python and working knowledge of C/C++.
- Experience in developing and customizing predictive and classification models.
- Hands-on experience with GPU accelerated AI development using NVIDIA GPUs.
- Familiarity with NVIDIA AI ecosystem (DeepStream, Triton Inference Server, TensorRT, or similar GPU optimization tools).
- Familiarity with video processing or streaming systems (GStreamer, FFmpeg, or similar).
- Experience with ML frameworks (PyTorch, TensorFlow, or equivalent) with GPU-based training workflows.
- Understanding of multiprocessing, multithreading, and performance optimization concepts.
- Knowledge of Reinforcement Learning, stream processing frameworks (Kafka/RabbitMQ), or edge/IoT deployment is a plus.
Placements (Choose one)
- Halim, East Jakarta.
- Cilandak, South Jakarta (Alamanda Office Tower 11th Floor).
- Umbulharjo, Yogyakarta.