We are working on different areas where AI/ML can help portfolio managers, researchers, risk managers, and other functions. Some examples are: enabling traders/researchers to consume vast amounts of research and literature by organizing, summarizing information, sometimes in near real-time, doing quantitative modeling to price instruments, modeling demand and supply of commodities and other fundamentals, modeling weather & optimizing algorithmic execution of trades and modeling and building simulations of risk, to name a few.

The AI/ML work spans usage of LLMs, deep learning, reinforcement learning and other ML techniques. The work also requires building AI/ML infrastructure for data wrangling, building feature stores, building frameworks for deployments, measurements, re-training, etc.

We are seeking an AI Engineering Lead who has experience with LLMs, deep learning, reinforcement learning, as well as an interest and ability to keep up with advancements in AI/ML. The candidate should also be strong in software engineering and be comfortable with AI/ML experimentation and productionization.

Key Responsibilities

• Lead and mentor a team of AI/ML engineers
• Define technical vision and roadmap for AI/ML initiatives
• Partner with stakeholders including portfolio managers, quants, and business teams to identify high-impact opportunities
• Architect and build scalable AI/ML solutions from experimentation to production
• Design AI/ML infrastructure including feature stores, deployment frameworks, and monitoring systems
• Establish best practices for model development, deployment, and evaluation
• Stay current with AI/ML advancements and apply them to business problems
• Drive hiring and professional development of team members

Required Qualifications

Technical

• Deep expertise in AI/ML including LLMs, deep learning, and reinforcement learning
• Strong computer science fundamentals
• Expert in Python and at least one other language (Java, C++, C#, etc.)
• Experience with cloud platforms (AWS, Azure, or Google Cloud)
• Hands-on experience with LLM techniques: prompt engineering, fine-tuning, PEFT, RAG
• Track record of building and deploying AI models at scale
• Experience with MLOps and production ML infrastructure

Leadership

• 3+ years leading AI/ML engineering teams
• Proven ability to mentor engineers and grow talent
• Strong communication skills with technical and non-technical stakeholders
• Experience delivering complex projects on time
• Comfortable balancing hands-on technical work with team leadership

Preferred Qualifications

• Advanced degree (MS/PhD) in Computer Science, AI, ML, or related field
• Experience in financial institutions or fintech
• Background in reinforcement learning, quant modeling, or algorithmic trading
• Publications, patents, or open-source contributions in AI/ML
• Experience building AI/ML platforms from scratch