Machine Learning Engineer

Few&Far; New York (NY); Sur place; USD 120 000 - 180 000; Plein temps

Résumé du poste

Few&Far in New York is seeking a Machine Learning Engineer to take models from experimentation to production, delivering practical, scalable solutions in a fintech context.

You will combine hands-on model development with the engineering required to keep models reliable, maintainable, and well-integrated with product teams. Your work will involve building data pipelines, evaluating models, and monitoring performance in production.

Qualifications

• Experience building and deploying machine learning models in a commercial environment.
• Strong programming skills with Python and related libraries, with emphasis on clean, maintainable code.
• Good understanding of data preparation, model evaluation, and trade-offs in modeling approaches.

Responsabilités

• Develop and evaluate machine learning models for real business problems.
• Prepare data and build pipelines to support training and deployment.
• Integrate models into products alongside software engineers.

Connaissances

Python

ML modeling

Data pipelines

Model deployment

Outils

TensorFlow

PyTorch

Scikit-learn

Description du poste

We are looking for a Machine Learning Engineer to join a scaling fintech, taking models from initial experimentation through to production.

You’ll combine hands-on model development with the engineering needed to make those models useful, reliable & maintainable.

What you’ll be working on:

• Developing and evaluating machine learning models against real business problems.
• Preparing data and building pipelines to support training & deployment.
• Integrating models into products alongside software engineers.
• Monitoring performance in production & improving models over time.

We'd love to speak to you if you have:

• Experience building and deploying machine learning models in a commercial environment.
• Strong programming skills with Python and Python libraries, with an emphasis on clean, maintainable code.
• A good understanding of data preparation, model evaluation and the trade-offs involved in choosing an approach.
• Experience working with engineering or product teams to deliver practical solutions.

Previous fintech experience is a plus, but isn’t essential. We’re interested in what you’ve built, the problems you’ve solved & where you’d like to go next.