Machine Learning Engineer
New York, NY, United States
Cantor Fitzgerald
Iconic global financial institution with world-class talent, providing specialized sector expertise, innovative products, and personalized solutions to clients across the globe.Qualifications
- Bachelor's degree in a technical subject (e.g. computer science, machine learning, mathematics, physics, statistics, econometrics), or equivalent experience
- Ability to write code fluently in at least one programming language, preferably Python
- Knowledge of mathematics, statistics and machine learning concepts needed to properly train and evaluate production models and understand research papers
- Ability to communicate technical ideas effectively and work with business partners
- Entrepreneurial mindset and strong interest in using LLMs and classical machine learning techniques to help drive a multi-billion dollar business
- 2+ years experience in a machine learning, data engineering or software engineering team
Nice To Have
- Familiarity with deploying and managing containerized applications in an AWS and/or Azure environment
- Familiarity with Infrastructure as Code (Terraform) and CI/CD
- Experience building RESTful APIs (preferably in Flask, FastAPI, or other Python frameworks)
- Experience building data pipelines to feed ML models
- Knowledge of Python ML/data/math libraries such as PyTorch, numpy and pandas
The expected base salary for this position ranges from $ 175,000 to $ 250,000. The actual base salary will be determined on an individualized basis taking into account a wide range of factors including, but not limited to, relevant skills, experience, education, and, where applicable, licenses or certifications held. In addition to base salary and a competitive benefits package, this position may be eligible for additional types of compensation including discretionary bonuses and other short- and long-term incentives (e.g., deferred cash, equity, etc.).
Tags: APIs AWS Azure CI/CD Computer Science Data pipelines Econometrics Engineering FastAPI Flask LLMs Machine Learning Mathematics ML models NumPy Pandas Physics Pipelines Python PyTorch Research Statistics Terraform
Perks/benefits: Career development Competitive pay Equity / stock options
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