Machine Learning Data Engineer Specialist

Prodigy Resources - Seattle, WA

Full-time - Mid Level

Seattle, WA

Administrative and Support Services

About the position

We are looking for a Senior Machine Learning Engineer to help us build a brand-new financial technology platform for the future. We seek individuals who operate like owners, who love to learn, possess grit, and act with integrity and empathy. We encourage applicants even if their experience doesn't precisely match the job description, as we value skills and passion that set candidates apart. We welcome diverse perspectives and individuals who are not afraid to challenge assumptions. In this role, you will be responsible for understanding business objectives and product requirements to develop machine learning algorithms that meet these goals. You will build prototypes and proof of concepts to assess feasibility and drive data-based decisions. Running experiments to evaluate performance and improvements will be a key part of your responsibilities, as well as providing innovative ideas and alternatives to enhance product features. You will define data and feature validation strategies, deploy models to production systems, and manage their operation, including monitoring and troubleshooting. Additionally, you will design, build, and manage data pipelines and infrastructure that collect, store, and process large volumes of transactional and customer data from various sources. Your role will also involve developing, deploying, and scaling machine learning models and applications in both production and lower environments, ensuring data quality, security, and availability for all data, notebooks, models, experiments, and applications. Integration of machine learning models with the SaaS platform and other services and tools, such as the model registry, feature store, data lake, and event streams, will be essential. Collaboration with data scientists to develop and test machine learning models is expected, as well as driving code reviews to ensure code quality, maintainability, and adherence to coding standards.

Responsibilities

• Understand business objectives and product requirements to develop ML algorithms that achieve them.
• Build prototypes and proof of concepts to determine feasibility and drive data-based decisions.
• Run experiments to assess performance and improvements.
• Provide ideas and alternatives to drive a product/feature.
• Define data and feature validation strategies.
• Deploy models to production systems and operate them, including monitoring and troubleshooting.
• Design, build, and manage data pipelines and infrastructure that collect, store, and process large volumes of transactional and customer data from various sources.
• Develop, deploy, and scale machine learning models and applications in production and lower environments.
• Ensure data quality, security, and availability for data, notebooks, models, experiments, and applications.
• Integrate ML models with the SaaS platform and other services and tools, such as the model registry, feature store, data lake, and event streams.
• Collaborate with data scientists to develop and test machine learning models.
• Drive code reviews to ensure code quality, maintainability, and adherence to coding standards.

Requirements

• A Bachelor's degree in Computer Science or equivalent education.
• 3+ years of relevant professional experience or an advanced degree such as a master's or PhD.
• Experience leading projects from architectural design to production while maintaining high standards of technical excellence across the team.
• Effective communication and collaboration skills, with a history of collaborating effectively with teams and cross-functional stakeholders.
• Experience with data management, data, and building pipelines.
• Experience with building and deploying machine learning models.
• Experience with AWS, Snowflake, Databricks, or similar technologies.