Machine Learning Engineer
5 days ago
Our organization is dedicated to revolutionizing financial technology through the application of Artificial Intelligence.
We're seeking a seasoned Machine Learning Engineer to spearhead the development of Ai-powered systems that drive our business forward.
As a Machine Learning Engineer at Deriv, you'll be responsible for designing and implementing advanced AI solutions that integrate seamlessly across our operational landscape, from trading algorithms to customer experience. Your key responsibilities will 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.
We are looking for a candidate with exceptional technical expertise and a track record of delivering impactful Ai solutions.
Technical Skills:
- 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, MLflow, Kubeflow, and Seldon for scaling Ai operations.
- Real-Time Processing: Hands-on experience with Flink, Kafka, and event stream processing for dynamic data workflows.
- Work on transformative Ai projects with real-world impact.
- Collaborate with an innovative and forward-thinking team.
- Competitive compensation and growth opportunities.
- Access to cutting-edge technologies and learning resources.
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