AI/ML Engineer

• Design, build, and maintain end-to-end AI and machine learning solutions for real-world use cases.
• Select and implement suitable approaches, including traditional machine learning, deep learning, and generative AI, based on problem requirements and constraints.
• Develop data processing, model training, evaluation, and inference pipelines, and integrate AI components with applications and APIs.
• Deploy and operate AI systems in production, with attention to scalability, testing, observability, and reliability.
• Measure and improve model and system performance, balancing accuracy, latency, resource usage, and cost.
• Collaborate with cross-functional stakeholders to define objectives, communicate technical decisions, and deliver measurable results.

• Strong proficiency in Python, software engineering principles, and service/API development and integration.
• Solid understanding of AI/ML fundamentals and large language models, including their capabilities, limitations, and practical applications.
• Hands-on experience building LLM-powered applications or AI agents, including tool calling, prompt design, and context management.
• Familiarity with RAG architectures, embeddings, information retrieval, and techniques for improving answer quality.
• Ability to design experiments, evaluate model outputs, analyze failures, and make quality-driven decisions.
• Strong problem-solving skills, ability to explain technical trade-offs, and ownership from implementation through delivery.

• Experience with agent development frameworks such as LangGraph or equivalent tools.
• Experience in monitoring and evaluating AI systems.
• Familiarity with financial or investment products.

If you enjoy building practical AI solutions, continuous learning, and solving challenging engineering problems, we would be glad to learn more about your experience and projects.