AI Systems Engineer

Careers Gdms, Pittsfield, MA

What you will do

Turn difficult program challenges into opportunities for innovation. Partner with engineers, program teams, and AI Champions to identify repetitive tasks, workflow bottlenecks, and complex problems where AI can make a meaningful difference.
Build, experiment, and improve. Design, develop, and refine AI-enabled tools, workflows, and processes, moving from a focused concept to a practical solution that meets real user needs.
Explore emerging capabilities. Test and evaluate new AI models, features, tools, and supporting frameworks when needed, with an emphasis on technical capability, integration, and solution development.
Make reliability and responsible use part of the design. Evaluate solutions for usefulness, accuracy, reliability, security, and suitability for their intended application; provide timely, constructive feedback on benefits, limitations, defects, and risks.
Demonstrate impact. Establish practical measures of success and show how your innovations save time, improve quality, reduce effort, or make information and workflows more accessible.

Posted pay

$91K–$101K

a year

This base pay is below the median for ML and AI engineering jobs in other US places with no level in the job title.

We compare the middle of each posted range. This is base pay as posted. The group does not include this job.

Location

Pittsfield, MA

Work type

Not given

Level

Not given

Experience

2+ years

Posted

14 days ago

Last check

7 h ago

Job type

ML / AI engineering

What you will do

Turn difficult program challenges into opportunities for innovation. Partner with engineers, program teams, and AI Champions to identify repetitive tasks, workflow bottlenecks, and complex problems where AI can make a meaningful difference.
Build, experiment, and improve. Design, develop, and refine AI-enabled tools, workflows, and processes, moving from a focused concept to a practical solution that meets real user needs.
Explore emerging capabilities. Test and evaluate new AI models, features, tools, and supporting frameworks when needed, with an emphasis on technical capability, integration, and solution development.
Make reliability and responsible use part of the design. Evaluate solutions for usefulness, accuracy, reliability, security, and suitability for their intended application; provide timely, constructive feedback on benefits, limitations, defects, and risks.
Demonstrate impact. Establish practical measures of success and show how your innovations save time, improve quality, reduce effort, or make information and workflows more accessible.