Our client is a leader in financial technology, focused on automating and optimizing operations with AI to drive innovation and scalability. They are seeking a skilled AI Engineer to develop cutting-edge AI-driven systems to support their business goals.
Responsibilities:
As an AI Engineer, you will design and implement AI solutions across key areas such as trading algorithms and customer experience. Responsibilities include:
- Modeling: Develop deep learning, reinforcement learning, and graph neural networks for predictive analytics and automated strategies.
- NLP: Implement NLP solutions for sentiment analysis, document processing, and customer interactions using tools like spaCy, Hugging Face, and OpenAI APIs.
- Vector Search: Build systems using vector databases (e.g., Weaviate, Pinecone, Milvus) for real-time data retrieval.
- MLOps: Deploy and maintain AI models using tools like MLflow, Kubeflow, and TensorFlow Serving.
- Data Engineering: Create high-performance data pipelines with Apache Spark, Kafka, and Hadoop.
- Generative AI: Integrate AI technologies (e.g., GPT, DALL-E, GANs) for innovative user experiences.
- Optimization: Utilize tools like Optuna and Ray Tune to maximize model performance.
Requirements:
- Proficient in Python, R, C++, or Java.
- Expertise in deep learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Solid experience with Pandas, NumPy, and vector databases like Weaviate, Pinecone, Milvus.
- Strong background in reinforcement learning using tools like OpenAI Gym, Ray RLlib, and Stable Baselines.
- Experience with Generative AI models, including GANs, StyleGAN, BigGAN, and transformer-based architectures.
- Hands-on with MLOps tools such as Docker, Kubernetes, MLflow, Kubeflow, and Seldon.
- Familiarity with real-time data processing tools such as Kafka, Flink, and Hadoop.
Preferred Qualifications:
- Advanced degree in Computer Science, Machine Learning, or related fields.