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Our client is a data-driven marketing technology company that builds advanced analytics, machine learning, and optimization solutions. Their platform processes large-scale data and powers critical business decisions through reliable production systems and workflows.
Overview
We are looking for a Senior Machine Learning Engineer to help build, maintain, and scale the infrastructure, workflows, and production systems that power machine learning and data-driven applications.
This is not a traditional Data Science role. Instead, it is focused on engineering, platform ownership, workflow orchestration, and production reliability.
The ideal candidate combines strong software engineering fundamentals with experience supporting machine learning systems in production environments.
You will work closely with Data Scientists, Engineers, and business stakeholders to build scalable workflows, maintain critical data infrastructure, and ensure the reliability of production systems.
Responsibilities
- Design, build, and maintain production-grade data and machine learning workflows.
- Develop and support workflow orchestration systems using tools such as Flyte, Airflow, Prefect, or similar platforms.
- Build and maintain scalable Python services and data processing pipelines.
- Create, optimize, and manage SQL-based data models and BigQuery workflows.
- Own production reliability, monitoring, observability, and operational excellence across ML systems.
- Collaborate with Data Scientists to deploy, maintain, and operationalize machine learning models.
- Build integrations between internal platforms, APIs, and data systems.
- Support Kubernetes-based environments and cloud-native infrastructure.
- Participate in code reviews, testing, CI/CD processes, and engineering best practices.
- Troubleshoot production issues and continuously improve system performance and reliability.
- Take ownership of projects from design through deployment and long-term maintenance.
Required Qualifications
- 4+ years of experience in Machine Learning Engineering, MLOps, Platform Engineering, Backend Engineering, or similar roles.
- Strong hands-on experience with Python and SQL.
- Experience building and operating production data or machine learning systems.
- Experience with workflow orchestration platforms such as Flyte, Airflow, Prefect, Metaflow, or similar tools.
- Familiarity with Kubernetes and modern cloud infrastructure.
- Strong understanding of software engineering best practices, including testing, CI/CD, version control, and code reviews.
- Experience working with monitoring, logging, observability, and production support.
- Ability to work independently and take ownership of technical projects end-to-end.
- Strong communication skills and experience collaborating across technical teams.
Preferred Qualifications
- Experience supporting machine learning platforms or MLOps environments.
- Experience with BigQuery and large-scale data processing.
- Experience working with marketing technology, attribution, forecasting, or analytics platforms.
- Exposure to LLM-powered applications, AI systems, or agentic workflows.
- Experience operating systems with strict reliability and performance requirements.
Schedule
- Full-time
- Monday–Friday
- 8:00 AM – 5:00 PM PST
Benefits
- Fully remote position.
- 11 US holidays.
- 3 weeks PTO.
- Performance-based bonus program.
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