Senior Platform Engineer, Machine Learning
About The Position
Movable Ink scales content personalization for marketers through data-activated content generation and AI decisioning. The world’s most innovative brands rely on Movable Ink to maximize revenue, simplify workflow and boost marketing agility. Headquartered in New York City with close to 600 employees, Movable Ink serves its global client base with operations throughout North America, Central America, Europe, Australia, and Japan. The AI Systems team owns the core recommendations engine that powers billions of AI-driven marketing decisions daily across some of the world's largest consumer brands. As a Senior Distributed Systems Engineer, you will lead the evolution of this system into a modern, scalable distributed architecture - one of the most impactful technical initiatives at Movable Ink. This is an opportunity to do deep distributed systems work on a production system that directly drives revenue for our customers, while shaping the technical direction of a team working at the intersection of systems engineering and machine learning.
Requirements
- 5+ years software engineering experience with a focus on distributed systems
- Deep experience building and operating large-scale distributed systems that are fault tolerant, highly available, and highly concurrent
- Exemplary software engineering skills (system design, unit testing, git, code review, CI/CD)
- Strong foundation in Python
- Experience with distributed data processing frameworks (e.g. Apache Spark, Apache Flink, Apache Beam); hands-on Spark experience is a plus
- Practical understanding of distributed systems fundamentals: consensus, partitioning, replication, back-pressure, idempotency, and failure handling
- Experience with a cloud provider e.g. AWS, Azure, GCP (we use Google Cloud Platform)
- Experience with modern distributed and microservice technologies (we use Kubernetes, Kafka, and gRPC)
- Familiar with Software Development Lifecycle practices, such as continuous integration/continuous delivery and automated deployment (we use Docker, Kubernetes, and GitHub Actions)
- Strong technical leadership skills with the ability to collaborate effectively, advocate for sound architectural decisions, and mentor other engineers
- Exceptional problem-solving skills, including the ability to efficiently identify, analyze, and resolve complex issues in production systems
- A willingness and eagerness to continuously learn, adapt to evolving technologies, and strive for personal and professional improvement
Responsibilities
- Lead the architectural evolution of the core recommendations pipeline to a modern distributed architecture, delivering incremental value while maintaining production stability
- Design, build, and operate scalable, fault-tolerant backend services that power personalization at scale across content selection, send-time optimization, subject line personalization, and frequency capping
- Identify and resolve performance bottlenecks, reliability risks, and scaling limitations across the system
- Collaborate with ML engineers and product stakeholders to translate requirements into rigorous technical designs with a clear path to production
- Own key system components end-to-end - from architecture and implementation to deployment, monitoring, and incident response
- Champion engineering best practices around system design, code quality, testing, observability, and operational excellence
- Mentor engineers and contribute to a culture of technical rigor, ownership, and continuous improvement
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
251-500 employees
