Machine Learning Platform Engineer

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Company Overview

A rapidly growing global live commerce marketplace is building technology that enables people to buy, sell, and discover products through interactive live shopping experiences. The organization operates across North America, Europe, and other global markets, supporting sellers across categories such as trading cards, fashion, electronics, and live plants.

The organization is developing infrastructure and products that support a rapidly evolving commerce ecosystem. Its engineering teams work across global hubs while emphasizing collaboration, rapid execution, user-focused development, and high-impact technical initiatives.

The organization is seeking a Machine Learning Platform Engineer to design and scale the core infrastructure powering machine learning and self-hosted large language model applications. This role will involve working closely with machine learning scientists to bring advanced models into production and develop new AI-powered product experiences.

The successful candidate will build dependable, high-performance systems for large-scale machine learning workloads, including low-latency model serving, distributed training, and high-throughput GPU inference.

Key Responsibilities

• Own the infrastructure powering AI and machine learning models across critical business areas, including growth, recommendations, trust and safety, fraud prevention, and seller tooling.
• Prototype, deploy, and productionize innovative machine learning architectures that directly influence user experiences and marketplace dynamics.
• Design and scale inference infrastructure capable of serving large models with low latency and high throughput.
• Build distributed training and inference pipelines using GPUs, model parallelism, and data parallelism.
• Collaborate closely with machine learning scientists to transition advanced models from research into reliable production systems.
• Develop infrastructure that improves the reliability, scalability, and performance of AI and ML applications.
• Take on complex technical challenges as AI capabilities expand across the broader technology ecosystem.
• Drive initiatives across multiple product areas and communicate technical findings and recommendations to leadership and product teams.
• Develop well-tested, reproducible systems suitable for large-scale production environments.
• Contribute to a collaborative engineering culture focused on innovation, ownership, and continuous improvement.

Required Qualifications

• 4+ years of professional experience developing machine learning systems and algorithms.
• Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, or a related technical field, or equivalent professional experience.
• 3+ years of software engineering experience building and maintaining production systems operating at consumer scale.
• 1+ years of professional experience developing software with Python.
• Ability to work autonomously and drive initiatives across multiple product areas.
• Strong communication skills with the ability to present technical findings to leadership and product teams.
• Experience working with operational, search, and key-value databases such as PostgreSQL, DynamoDB, Elasticsearch, and Redis.
• Strong understanding of visualization and monitoring tools such as Datadog and Grafana.
• Familiarity with cloud computing platforms and managed services, including AWS SageMaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Apache Kafka, and Flink.
• Ability to collaborate effectively in a remote working environment.
• Strong commitment to well-tested, reproducible engineering practices.
• Exceptional documentation and communication skills.

Work Arrangement

The role offers flexibility to work from home or from designated global office hubs. Team members in this position are expected to live within commuting distance of the San Francisco, New York, Los Angeles, or Seattle hubs. The organization values in-person collaboration for planning, problem-solving, and team connection.

Disclaimer

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