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As an AI Engineer at Deriv, you will design and implement advanced AI solutions, integrating them across all operational facets, from trading algorithms to customer experience. Key responsibilities include:
- Advanced Modeling: Develop and deploy deep learning, reinforcement learning, and graph neural networks for predictive analytics, automated trading strategies, and decision-making systems.
- NLP Applications: 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 .
- Vector Search and Semantic Retrieval: Build systems utilizing vector databases like Weaviate , Pinecone , and Milvus to enable real-time, context-aware data retrieval.
- Agentic Systems: Design autonomous and multi-agent systems for dynamic decision-making and complex task management in trading environments.
- MLOps Integration: Deploy and maintain AI models at scale using tools such as MLflow , Kubeflow , TensorFlow Serving , and Seldon for seamless production workflows.
- Big Data Engineering: Architect high-performance data pipelines using Apache Spark , Kafka , and Hadoop for real-time and batch processing.
- Generative AI: Explore and integrate generative technologies, including GPT , DALL-E , and GANs , for innovative applications in user experience and content generation.
- Transformers and Architectures: Utilize advanced transformer models like BERT , T5 , and ViT to solve complex problems in NLP and computer vision.
- Explainability and Fairness: Incorporate tools like SHAP , LIME , and Fairlearn to ensure AI systems are transparent, interpretable, and unbiased.
- Optimization: Use advanced hyperparameter tuning tools like Optuna and Ray Tune to maximize model performance.
- Cloud and Edge AI: Implement scalable AI systems on cloud platforms (AWS, Google Cloud, Azure) and optimize for edge computing with TensorFlow Lite and NVIDIA Jetson .
- Programming Expertise: Proficiency in Python , R , C++ , or Java .
- Deep Learning Frameworks: Expertise in TensorFlow , PyTorch , and scikit-learn .
- Data Tools: Experience with Pandas , NumPy , and HDFS for data analysis and storage.
- Vector Databases: Knowledge of Weaviate , Pinecone , Milvus , or Annoy for similarity-based retrieval systems.
- Reinforcement Learning: Experience with tools like OpenAI Gym , Ray RLlib , and Stable Baselines .
- Generative AI Models: Familiarity with GANs , StyleGAN , BigGAN , and transformer-based models for various applications.
- MLOps and Automation: Proficiency in Docker , Kubernetes
Key Skills
Ranked by relevance
ai
tensorflow
cloud
deep learning
mlops
neural networks
computer vision
data analysis
big data
kubeflow
storage
pytorch
python
docker
apache
pandas
hadoop
mlflow
kafka
numpy
spark
java
aws
c
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- Posted
- Jan 02, 2025
- Type
- Full-time
- Level
- Entry
- Location
- Dubai
- Company
- Deriv
Industries
Financial Services
Categories
Engineering
Information Technology
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