Machine Learning Engineer, Senior Associate

Shape the future of technology and drive significant business impact in financial services. Join our team and help us develop game changing, high-quality solutions.

• Lead the design, development, and deployment of generative AI solutions, ensuring alignment with business objectives and technical requirements.
• Demonstrate deep expertise in generative AI technologies, contributing to the development of POCs and evaluating new methodologies to enhance AI capabilities.
• Exhibit strong proficiency in Java or Python, with the ability to architect and build complex AI models from scratch. Ensure the delivery of secure, high-quality production code and utilize experience with React or Angular to create intuitive user interfaces for AI applications. Conduct thorough code reviews to maintain high standards of code quality.
• Leverage AWS experience to implement best practices in AI integration, ensuring quality, security, and efficiency across AI projects.
  Identify and implement opportunities to automate processes and enhance the operational stability of generative AI applications and systems.
• Actively participate in communities of practice to promote the adoption and awareness of new generative AI technologies, fostering a culture of continuous innovation.

• Minimum 5+ years of strong proficiency in Python or Java, with the ability to architect and build complex AI models from scratch.
• Two years of experience in generative AI development and prompt engineering.
• Proven experience in system design, application development, testing, and operational stability in AI projects.
• Minimum 5+ years of strong experience with React or Angular with minimum 2+ years of AWS experience.
• Understanding of agile methodologies such as CI/CD, Application Resiliency, and Security, applied to AI projects.
• Experience with LLM models and agentic tools.

• Experience with AI model optimization and performance tuning to ensure efficient and scalable AI solutions.
• Familiarity with data engineering practices to support AI model training and deployment.
• Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning with experience with AI/ML libraries and tools such as Tensor Flow, PyTorch, Scikit-learn, and Keras.