Junior MLOps Engineer: AI/ML & Automation

SimVentions, Inc - Glassdoor 4.6; Mesa (AZ); On-site; USD 79,000 - 110,000; Full time

Benefits offered by this job

Employee Ownership

Family focus

Culture of excellence

Dress code: Business casual

Training opportunities

Employee appreciation

Job summary

SimVentions is seeking a junior to mid-level software developer for the Machine Learning Operations (MLOps) project in a dynamic, employee-owned environment. Location in Mesa, AZ with minimal travel and a requirement for interim Secret Clearance.

You will expand automation capabilities and optimize model training pipelines using Go, Python, JavaScript, and Vue.js. Ideal candidates have foundational AI/ML knowledge, experience with containers (Docker), databases (MongoDB, PostgreSQL), and SDK/API

Qualifications

• Hands on experience with Go, Python, JavaScript and Vue.js.
• Experience with data storage and retrieval using databases, S3 or similar storage.
• Foundational AI/ML knowledge including model lifecycle (training, validation, deployment, monitoring).
• Understanding CPU/GPU use for ML and model training.
• Experience integrating toolsets via SDKs and APIs.

Responsibilities

• Expand and automate the MLOPS ecosystem within existing development environments.
• Automate model training processes for repeatability and scalability.
• Design architecture that scales data sources and model outputs.
• Inject configuration management of data sources and model outputs.

Skills

Go

Python

JavaScript

Vue.js

AI/ML knowledge

SDKs & APIs

Education

BS in engineering/computational/technical field

Tools

MongoDB

PostgreSQL

S3 storage

Job description

SimVentions is seeking a junior to mid-level software developer for the Machine Learning Operations (MLOps) project in a dynamic, employee-owned environment. Location in Mesa, AZ with minimal travel and a requirement for interim Secret Clearance.

You will expand automation capabilities and optimize model training pipelines using Go, Python, JavaScript, and Vue.js. Ideal candidates have foundational AI/ML knowledge, experience with containers (Docker), databases (MongoDB, PostgreSQL), and SDK/API