Senior Staff Machine Learning Engineer

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 2025 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?

Position Overview

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.

Responsibilities

• 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, and ensuring models meet business objectives.
• Leverage distributed computing frameworks and cloud-based platforms to process large-scale datasets efficiently.
• Stay up-to-date with the latest advancements in machine learning, software engineering practices, and deployment strategies to keep our systems cutting-edge.

Key Qualifications

• Master’s or Ph.D. in Computer Science, Engineering, or a related field.
• 6+ years of experience as a Machine Learning Engineer, with expertise in building and deploying machine learning models in production environments.
• Strong proficiency in Python, or similar programming languages, and experience with ML libraries like TensorFlow, PyTorch, and scikit-learn.
• Extensive experience with cloud platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks (e.g., Spark, Kubernetes).
• Proven track record of implementing end-to-end machine learning pipelines, from data preprocessing to production deployment and monitoring.
• Strong background in model optimization, version control, and CI/CD practices for machine learning.
• Excellent problem-solving abilities and the capacity to collaborate with cross-functional teams to deliver high-quality, production-ready systems.

Compensation

The salary compensation range for this role will be commensurate with the candidate's experience and Flex's internal leveling guidelines and benchmarks.

• For working locations in NY/NJ/CA: The base salary pay range will be $209,000 - $225,000.
• For all other states: The base salary pay range will be $188,000 - $203,000.

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Company Information

Flex is a growth-stage, NYC headquartered FinTech company creating the best rent payment experience. We empower renters with flexibility over their most significant recurring expense.

Life at Flex

We understand that it takes a diverse team of highly intelligent, curious, determined, empathetic, and self-aware people to grow a successful company. Our HQ is located in New York City, but we have employees located throughout the US, Australia, Canada, and South America. We are growing quickly, but deliberately, with a focus on building an inclusive culture. Our dynamic team has incredible perspectives to share, just as we know you do.