Job Description

AI Engineer
Millennium is a cutting edge fintech where we solve hard and interesting problems at the intersection of computer science, finance, and mathematics. We are focused on innovating and rapidly applying innovations to real world scenarios in finance. This enables engineers to work on interesting problems, learn quickly and have deep impact to the firm and the business.


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 amount of research and literature by organizing, summarizing information, sometimes in near real-time; doing quantitative modeling to find prices of instruments, modeling demand and supply of commodities and other fundamentals; modeling weather, optimizing algorithmic execution of trades; 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 a senior AI/ML SWE who has experience with LLM, deep learning, reinforcement learning, etc. 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 product ionization.

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. * 7+ years of relevant experience.