Senior Software Engineer, 1

meredith; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

People Inc. is seeking a Senior Software Engineer 1 to join its AI/ML Engineering Platform team. You will help design and build scalable distributed systems and ML pipelines that power search, ranking, and personalization across our platforms.

You will work with Vertex AI Pipelines, KServe, Kafka, Elasticsearch, and Milvus to train and deploy models, build APIs with FastAPI, and monitor data quality and performance in production.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field

Responsibilities

• Design and build scalable backend systems and ML pipelines for search, retrieval, ranking, and personalization
• Develop and maintain data pipelines for feature generation, model training, and analytics workflows
• Own production systems and ensure reliability and performance across indexing, retrieval, and serving layers
• Collaborate with data scientists and product teams to deliver ML-driven features
• Create and maintain documentation for pipelines, models, APIs, and system design

Skills

Python

Node.js

TypeScript

Kafka

REST APIs

GraphQL

Docker

Kubernetes

AWS

GCP

Elasticsearch

Milvus

Vertex AI

FastAPI

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Kafka

Apache Kafka

Vertex AI Pipelines

KServe

Milvus

FastAPI

Docker

Kubernetes

Elasticsearch

Job description

Job Title Senior Software Engineer, 1

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. Apply them where they make practical impact

The Role's Minimum Qualifications and Job Requirements

Education:

• Bachelor's degree in Computer Science, Engineering, or a related field

Experience:

• You have a strong foundation in modern backend and ML engineering practices and continue to learn and evolve. You bring:
• 6+ years of experience building scalable backend systems and services
• 5+ years of experience developing software using object oriented languages, with strong proficiency in Python, Node.js, and TypeScript
• Hands on experience with ES for search, indexing, and relevance tuning
• Experience with event driven systems using Apache Kafka for real time data pipelines and processing
• Strong understanding of version control systems including Git and platforms like Bitbucket
• Experience with observability and monitoring tools such as Grafana, Kibana, and APM
• Familiarity with cloud platforms including AWS and GCP, along with containerization using Docker and orchestration with Kubernetes
• Comfortable deploying, versioning, and monitoring models in production
• Curiosity to learn new technologies, especially in AI, LLMs, and modern search and recommendation systems, with a focus on applying them in real production use cases.
• Experience designing and building data pipelines using Apache Beam and Apache Airflow for ingestion, transformation, and feature pipelines
• Familiarity with experimentation and analytics tools such as Jupyter Notebook and Apache Spark to track and reproduce experiments
• Strong experience designing and consuming RESTful and GraphQL APIs, including versioning, documentation, and security practices like OAuth and JWT
• Good understanding of machine learning concepts including supervised learning, unsupervised learning, deep learning, and natural language processing, with practical application in ranking, retrieval, and personalization
• Beginner level experience managing ML pipelines using Vertex AI Pipelines for training, evaluation, and deployment workflows
• Ability to review code, provide clear feedback, and improve overall engineering quality
• Strong communication skills. Able to explain technic