Computer Vision and Machine Learning Expert
7 days ago
We are a cutting-edge company in the financial technology industry, revolutionizing CFD trading through AI.
Our team is composed of highly skilled professionals who share a passion for innovation and excellence.
We are looking for a highly skilled AI engineer to join our team and contribute to our mission of delivering unparalleled performance, innovation, and scalability.
The ideal candidate will have expertise in programming languages such as Python, R, C++, or Java, and will be experienced in deep learning frameworks like TensorFlow, PyTorch, and scikit-learn.
- Lead the development of AI systems: Design and implement deep learning, reinforcement learning, and graph neural networks for predictive analytics, automated trading strategies, and decision-making systems.
- NLP and Vector Search: Implement state-of-the-art NLP solutions for sentiment analysis, document processing, and customer interaction enhancements using tools like spaCy, Hugging Face Transformers, and OpenAI APIs. Build systems utilizing vector databases like Weaviate, Pinecone, and Milvus to enable real-time, context-aware data retrieval.
- Agentic Systems and MLOps: Design autonomous and multi-agent systems for dynamic decision-making and complex task management in trading environments. Deploy and maintain AI models at scale using tools such as MLflow, Kubeflow, TensorFlow Serving, and Seldon for seamless production workflows.
- Big Data Engineering and Generative AI: Architect high-performance data pipelines using Apache Spark, Kafka, and Hadoop for real-time and batch processing. Explore and integrate generative technologies, including GPT, DALL-E, and GANs, for innovative applications in user experience and content generation.
- Transformers and Explainability: Utilize advanced transformer models like BERT, T5, and ViT to solve complex problems in NLP and computer vision. Incorporate tools like SHAP, LIME, and Fairlearn to ensure AI systems are transparent, interpretable, and unbiased.
- Optimization and Cloud AI: Use advanced hyperparameter tuning tools like Optuna and Ray Tune to maximize model performance. Implement scalable AI systems on cloud platforms (AWS, Google Cloud, Azure) and optimize for edge computing with TensorFlow Lite and NVIDIA Jetson.
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