Hybrid Senior ML Engineer for AI Platform & LLM Apps

Kelly Services; Boston (MA); Hybrid; USD 110,000 - 124,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Paid vacation and personal time

401(k) retirement plan

Job summary

Kelly Services in Boston is seeking a Senior Machine Learning Engineer to design scalable AI platforms and autonomous workflows in a hybrid role.

You will guide research tools, RAG systems, LLM applications, and production-ready pipelines, collaborating with security and platform teams to improve reliability and performance.

This hands-on engineering position focuses on building and deploying AI capabilities for an enterprise information environment.

Qualifications

• Deep knowledge of ML systems and autonomous agent design.
• Hands-on experience building LLM applications and retrieval-augmented generation solutions.
• Practical experience with vector search technologies and vector data stores.
• Familiar with production ML operations, monitoring, and deployment practices.
• Strong Python development skills.
• Working knowledge of AWS infrastructure and Kubernetes environments.

Responsibilities

• This is a highly hands-on engineering position.
• Create, productionize, and maintain sophisticated AI and ML capabilities for enterprise research applications.
• Architect and enhance distributed machine learning services and scalable platform components.
• Build agentic applications, semantic retrieval pipelines, and supporting orchestration frameworks.
• Partner with software, platform, and security teams to deliver dependable, secure, and high-performing AI systems.

Skills

ML systems

Autonomous agents

LLM applications

Vector search

MLOps

Python

AWS

Kubernetes

Education

Bachelor's degree or higher in computer science, engineering, data science, or related

Tools

Python

AWS

Kubernetes

Vector search technologies

Job description

Kelly Services in Boston is seeking a Senior Machine Learning Engineer to design scalable AI platforms and autonomous workflows in a hybrid role.

You will guide research tools, RAG systems, LLM applications, and production-ready pipelines, collaborating with security and platform teams to improve reliability and performance.

This hands-on engineering position focuses on building and deploying AI capabilities for an enterprise information environment.