MCS is thrilled to be partnering with a global financial institution in NYC, as they look to add to their growing Machine Learning team. We're looking for a sharp, hands-on technologist with a passion for greenfield development and building products from scratch. If you're excited about large language models (LLMs), classic ML techniques, and building tools that power a multi-billion dollar enterprise, this role is for you. This team acts more as a startup within a financial institution, so experience in a startup environment (wearing multiple hats, build things from scratch, collaborating with the business, etc) will go a long way in this role. What You'll Need A bachelor's degree in a technical discipline (computer science, machine learning, mathematics, physics, statistics, econometrics), with a Masters preferred A true Engineering background in at least one programming language, with a strong preference for Python A deep understanding of math, statistics, and ML fundamental's; you should be comfortable training models, evaluating performance, and parsing technical research Strong communication skills with the ability to translate complex technical ideas into clear business impact An entrepreneurial approach, self-starter attitude, and eagerness to solve complex problems with innovative ML solutions Experience in a machine learning, data engineering, or software engineering environment Bonus Points For Experience with deploying and managing containerized applications in cloud environments (AWS and/or Azure) Familiarity with Infrastructure as Code tools like Terraform, and CI/CD pipelines Experience developing RESTful APIs using frameworks like Flask or FastAPI Building and maintaining data pipelines that serve ML systems Hands-on experience with Python libraries such as PyTorch, NumPy, and pandas Work Setup This role follows a hybrid model, three days in the office/two days remote Skills: Python Machine Learning LLM IaaC Terraform RESTful APIs Benefits: Annual bonus