AI Engineer Lead
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
Technical
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
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
- 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
- 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