Flex
FinTech
Sr.StaffMachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Sr. Staff Machine Learning Engineer at Flex. Skills: Machine Learning, MLOps, Production deployment. Own end-to-end lifecycle of ML projects. Build data pipelines”
Industry & Context.
Problem-solving abilities
What You'll Do.
Own end-to-end lifecycle of ML projects
Maintain data pipelines
Optimize data pipelines
Implement ML algorithms
Collaborate with data scientists
Collaborate with engineers
Collaborate with product teams
Monitor model performance
Improve model performance
Leverage distributed computing frameworks
Leverage cloud platforms
How You'll Work.
Team & Collaboration
Cross-functional teams; Product teams; Data scientists; Engineers
Full Job Description
Flex is a growth-stage, NYC headquartered FinTech company that is creating the best rent payment experience. It’s hard to believe that it’s 2026 and paying rent on time is expensive, inflexible, and difficult. We’re here to change that! Flex enables our users to pay rent throughout the month on a schedule that better fits their finances and budget. Our mission is to empower as many renters as possible with flexibility over their most significant recurring expense. After deliberately keeping a stealth profile as we built up unprecedented investor support and an enthusiastic user base, we are looking for motivated individuals to help us keep our mission growing. Will you be a part of the team? About the role We are seeking an experienced Senior Staff Machine Learning Engineer to join our dynamic team and take a leading role in developing cutting-edge machine learning systems that drive business growth. As a key technical contributor, you will drive the development, deployment, and scalability of machine learning models in a production environment, ensuring they deliver value and performance at scale. You will collaborate closely with data scientists, product teams and engineers to implement state-of-the-art solutions that power our products and services through continuous innovation. What you’ll do Own the end-to-end lifecycle of machine learning projects, from data collection and preprocessing to model deployment, monitoring, and maintenance in a production environment. Build, maintain, and optimize robust data pipelines that support model development, training, and deployment at scale. Implement machine learning algorithms and models that meet performance, scalability, and reliability requirements in a production setting. Collaborate with data scientists, engineers, and product teams to design and deploy machine learning systems that address business and product needs. Continuously monitor and improve model performance, conducting experiments, tuning hyperparameters
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