Senior Machine Learning Engineer

Role overview A senior individual-contributor role on the Data team of a commerce media infrastructure company, focused on designing, building, and operating the production machine learning systems that power personalization, recommendations, optimization, and decisioning. The role spans the full ML lifecycle, from experimentation and feature pipelines through deployment, monitoring, and ongoing operation, with substantial influence on ML architecture and engineering standards. The position reports to the Director of Data & Platform and is remote within the U.S.

Responsibilities - Design, build, and operate end-to-end ML systems across batch and real-time workloads, including feature generation, training, evaluation, deployment, inference, and retraining. - Develop production capabilities for personalization, recommendations, ranking, optimization, contextual decisioning, experimentation, and measurement. - Build reusable ML platforms, pipelines, frameworks, and tooling that improve reproducibility, self-service, reliability, and development speed. - Own the operational lifecycle of production models, including observability, data and model quality, drift detection, monitoring, failure handling, retraining, and governance. - Partner with ML practitioners to convert prototypes and research into maintainable systems, and with Data and Product teams to integrate those systems into the broader platform. - Provide technical leadership for ML architecture and distributed systems, balancing model performance, reliability, scalability, and operational complexity.

Requirements - 8+ years of professional software engineering or machine learning engineering experience. - Strong track record of building, deploying, and operating ML systems in production. - Solid software engineering fundamentals, including system design, APIs, testing, deployment, observability, and maintainable production code. - Experience designing distributed systems, large-scale data-processing workflows, or high-throughput and low-latency services. - Fluency across the ML lifecycle, including data and feature pipelines, training, evaluation, serving, monitoring, and retraining. - Ability to investigate production issues across models, data, application code, and infrastructure. - Strong collaboration and communication skills across ML, data engineering, analytics, and product disciplines. - U.S. core business hours availability and willingness to travel for company meetings.

Nice to have - Experience with personalization, recommendation, ranking, optimization, experimentation, measurement, or real-time decisioning systems. - Familiarity with Python, Apache Spark, Databricks, MLflow, feature stores, or model-serving platforms. - Experience operating ML workloads on AWS, Kubernetes, Amazon EKS, or infrastructure managed through Terraform. - Background building ML systems at enterprise, transaction-intensive, or regulated scale.

Benefits and work setup - Remote-first U.S. position with pay range of $160,000–$190,000 USD. - Flexible PTO with a minimum of one day off per quarter and ten days per year. - 11 federal holidays observed, plus additional days for Black Friday and Christmas Eve. - Health, dental, and vision insurance. - 401(k) with employer match. - Coworking space and WFH setup reimbursement. - Company offsites for planning, team-building, and networking.