Staff Machine Learning Engineer

New York, New York

Machine Learning

Permanent

Our client, an exciting Series B FinTech Startup, is hiring a Staff Machine Learning Engineer to join the team remotely. The successful candidate will design and deploy advanced machine learning models to help build interpretable, high-performing and scalable solutions leveraging data from AWS and Snowflake environments to drive impactful, data-informed decisions.

Responsibilities

Designing, developing and deploying machine learning models to support predictive analytics across key fintech applications.
Collaborating closely with cross-functional teams, including Data, Engineering and Product, to deliver integrated, data-driven solutions.
Ensuring high model performance and reliability through robust data pipelines and scalable infrastructure.
Converting model outputs into actionable insights that drive business strategy and financial inclusion outcomes.
Mentoring and supporting fellow team members to promote a culture of technical excellence and collaboration.
Championing best practices in MLOps, data governance and regulatory compliance across the ML lifecycle.

Skillset

PhD or Master’s degree in Computer Science, Mathematics, Statistics or similar.
10+ years of relevant experience in applying AI/ML techniques within the financial services or fintech sectors.
Extensive experience developing and deploying machine learning models for tasks such as classification, regression and forecasting.
Strong programming proficiency in Python and SQL.
Hands-on experience with AWS, particularly SageMaker and Bedrock, for model training, deployment and fine-tuning.
Familiarity with model lifecycle tools like MLflow, SageMaker Model Registry or similar platforms.
Practical experience using PyTorch, Scikit-learn and Generative AI models.
Knowledge of Large Language Models (LLMs) and frameworks such as Hugging Face, LangChain or Mirascope.
Solid understanding of cloud-based data architecture, including Snowflake, Amazon S3 and PostgreSQL.
Background working in FinTech, PropTech or startup environments is a bonus.