Senior Machine Learning Engineer, Fulfillment

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Design, develop, and deploy machine learning models and services for Enterprise AI products and business initiatives.

• Manage the entire machine learning lifecycle, from problem definition and data preparation to deployment and performance monitoring.

• Create reliable, scalable, and maintainable software using Python and associated technologies.

• Collaborate with product, engineering, data science, and business stakeholders to establish success metrics, prioritize tasks, and deliver effective solutions.

• Develop and maintain machine learning services on cloud infrastructure, ensuring monitoring, alerting, observability, and production safeguards are in place.

• Employ experimentation, statistical analysis, and causal or counterfactual evaluation to evaluate model quality and influence launch decisions.

• Participate in design reviews, architecture discussions, and the assessment of modeling and infrastructure trade-offs.

• Share expertise, mentor colleagues, enhance development practices, and engage in operational support for essential services.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related technical field, or equivalent practical experience.

• Five or more years of professional experience in developing and deploying machine learning models or systems in production environments.

• Proficiency in Python and SQL.

• Experience in production-quality coding, including automated testing, profiling, debugging, and code review.

• Familiarity with the complete machine learning lifecycle, encompassing data preparation, feature engineering, model evaluation, experimentation, deployment, and production monitoring.

• Experience in building and operating machine learning services or data products within Google Cloud Platform, Amazon Web Services, or a comparable cloud environment.

• Knowledge of containerized services and production software development practices, including Docker, continuous integration, monitoring, alerting, and incident response.

• Capability to collaborate with product, engineering, data science, and business stakeholders to define requirements and deliver measurable outcomes.

🏝️ Benefits

• New hire equity grant.

• Annual refresh grants.

• Flexible work location: home, office, or coffee shop.

• Regular in-person events.

• Market-competitive compensation and benefits.