Software Engineer, 1
Senior Software Engineer to work on AI/ML Engineering Platform, leveraging technologies like Vertex AI pipeline, Kafka, Elasticsearch, and Vector Database to build AI and ML capabilities for content recommendation and more.
Job Title
Job Description
About The Team:
People Inc. is looking for a Senior Software Engineer 1 to join our AI/ML Engineering Platform team. As part of the AI/ML Engineering Platform team, you'll be working on widely used components that help users find ways to consume content on our sites. This includes using technologies such as Vertex AI pipeline, KServe, Kafka, Elasticsearch and Vector Database to leverage the power of AI and ML use cases and build capabilities to recommend related articles, and much more!
As a Senior Software Engineer 1, you will collaborate with product owners, Data Science, Platform teams, project managers, and software engineers to create service applications and contribute to the technical roadmap
About The Positions Contributions:
Accountabilities, Actions and Expected Measurable Results ( 70%)
You understand how to design and build scalable distributed systems, backend platforms, compatible with AI/ML infrastructure for search, retrieval, ranking, recommendation, and personalization use cases
You will:
Design and build systems, manage scalable ML pipelines using Vertex AI Pipelines for training, evaluation and deployment to support ranking, retrieval, and recommendation personalization use cases
Develop and maintain data pipelines that support feature generation, model training, and analytics workflows. Own vector generation via Milvus, storage, and retrieval workflows
Implement model serving solutions using KServe and build APIs using FastAPI for low latency inference
Build observability and monitoring for models and pipelines. Track performance, drift, failures, and data quality issues
Collaborate with data scientists, product managers, and platform teams to define and deliver ML driven features
Investigate production issues across data pipelines, models, and services. Identify bottlenecks and improve reliability and performance
Create and maintain clear documentation for pipelines, models, APIs, and operational processes
Develop internal tools and dashboards to provide visibility into data processing and model behavior for stakeholders
Contribute to engineering standards, code quality, and best practices across Python-based services and ML systems
Stay current with ML infrastructure, MLOps practices, and relevant tools. Bring in improvements where they add clear value
Collaborate with product, data science, and frontend teams to deliver high quality search and feed experiences (30%)
Own production systems. Debug issues across indexing, retrieval, ranking, and serving layers
Create clear documentation for pipelines, models, APIs, and system design
Contribute to best practices for Python based ML systems, API design, and scalable infrastructure
Stay current with advancements in search, ranking, and recommendation systems. Appl
Posted June 7, 2026