Applied Artificial Intelligence Machine Learning Lead - Vice President

What you'll do

• Collaborate with AI/ML teams, business and product partners, and colleagues to align on AI capabilities and deliver solutions.
• Architect and implement ML- and LLM-powered solutions, data pipelines, and model inference services.
• Experiment, develop, and productionize machine learning models, services, and platforms in public cloud infrastructure.

What they ask for

• MS in Computer Science, Statistics, Mathematics, or Machine Learning.
• Minimum 7 years of development experience, including at least 4 years working on AI solutions.
• Experience using LLMs to solve business problems, including tracing, evaluations, and guardrails; strong Python programming skills and knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics.
• Ability to design end-to-end solutions, with knowledge of scalable and secure architecture, data management, and real-time processing with SQL and NoSQL stores; demonstrated leadership and communication skills.

Nice to have

• Financial-domain experience at a large institution in Asset and Wealth Management, Brokerage, or Investment Banking; LLM fine-tuning and small language model inference.
• Full-stack development using modern JavaScript and TypeScript frameworks; Go or Rust; expertise in AWS, Azure, or Kubernetes.

Tools

Python, OpenAI, Anthropic, Postgres, OpenSearch, Redis, AWS, Azure

AI focus

Develops and deploys machine learning and LLM solutions, including model inference services and GenAI-based solutions; work with tracing, evaluations, and guardrails.