Posted 17 days ago
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Seeking an AI/ML software engineer to design, experiment with, and productionize models and infrastructure that support portfolio managers, researchers, risk managers, and traders. Work spans LLMs, deep learning, reinforcement learning and classical ML for tasks such as summarization of research, quantitative pricing, simulation of risk, and execution optimization. Role requires strong software engineering skills, experience with cloud platforms, proficiency in Python and another language, and the ability to build data/ML infrastructure, feature stores, and deployment pipelines.
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Currency: Not specified
Full Job Description
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; modeling and building simulations of risk.
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 a AI/ML SWE 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
- Engage and collaborate with business stakeholders, quants, and other market researchers to deeply understand the problem space.
- Experiment, iterate, productionize AI/ML solutions.
- Build supporting data and AI/ML infrastructure and tools.
Required Skills and Qualifications
- Strong knowledge of the latest advancements in AI and machine learning.
- Strong fundamentals in computer science.
- Proficiency in Python and at least 1 other language such as Java, C++, C#, etc.
- Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud).
- Experience with using LLMs and with techniques such as prompt engineering, PEFT, fine-tuning, etc.
- Ability to build and evaluate AI models and tools using quantifiable metrics.
- Excellent problem-solving skills and ability to work independently as well as part of a team.
- Strong communication skills to effectively collaborate with developers and other stakeholders.
- Adaptable and willing to work in a start-up-like environment within a major institution.
Preferred Qualifications
- Advanced degree in Computer Science, AI, Machine Learning, or a related field.
- Experience in developing AI solutions for financial institutions.
- Knowledge of additional programming languages and frameworks.
