Our client is at the forefront of financial technology, revolutionizing CFD trading through AI-driven innovations. They focus on automating and optimizing operational processes to achieve unparalleled performance, scalability, and innovation. They are seeking a highly skilled AI Engineer to lead the development of sophisticated AI-driven systems that will drive their business forward.

Responsibilities:
The AI Engineer will design and implement advanced AI solutions, integrating them into diverse operational areas such as trading algorithms and 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 natural language processing 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 using vector databases such as 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 address 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: Leverage hyperparameter tuning tools such as Optuna and Ray Tune to enhance model performance.
• Cloud and Edge AI: Implement scalable AI systems on cloud platforms (AWS, Google Cloud, Azure) and optimize for edge computing using TensorFlow Lite and NVIDIA Jetson.

Requirements:
The ideal candidate will possess exceptional technical expertise and a strong 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.
• MLOps and Automation: Proficiency in Docker, Kubernetes, MLflow, Kubeflow, and Seldon.
• Real-Time Processing: Hands-on experience with Flink, Kafka, and event stream processing.

Soft Skills:

• Strong problem-solving and critical-thinking abilities.
• Effective collaboration across teams.
• Proven ability to deliver under tight deadlines.

Preferred Qualifications:

• Advanced degree in Computer Science, Machine Learning, or related fields.

Why Join Our Client?

• Opportunity to work on transformative AI projects with real-world impact.
• Collaboration with an innovative and forward-thinking team.
• Competitive compensation and growth opportunities.
• Access to cutting-edge technologies and learning resources.