- We are seeking an AI Engineer who will design, build, and deploy advanced machine learning and deep learning models tailored for production-scale systems.

- The role requires working closely with product, engineering, and data teams to translate complex business problems into AI-driven solutions.

- Candidates should have hands-on experience with frameworks like TensorFlow, PyTorch, or JAX, and must be adept at developing custom architectures beyond pre-trained models to suit problem-specific requirements.

- Strong knowledge of NLP, computer vision, or generative AI will be highly valued depending on project needs.

- Proficiency in writing optimized, scalable code in Python is expected, with additional exposure to languages like C++ or Java being advantageous.

- Understanding of distributed systems, GPU acceleration, and model optimization for latency-sensitive environments is critical.

- Experience with MLOps tools such as MLflow, Kubeflow, or Vertex AI is required to streamline deployment, monitoring, and retraining pipelines.

- Practical exposure to data engineering concepts, including feature store design and data versioning, will be appreciated.

- The role involves experimentation with novel architectures, staying current with research advancements, and rapidly prototyping ideas for validation.

- Candidates must demonstrate strong problem-solving skills, an ability to balance research depth with delivery timelines, and a mindset for building AI systems that are explainable, ethical, and production-ready.