Associate AI/ML Software Engineer (Hybrid)

Venerable; Glenloch (PA); Hybrid; USD 90,000 - 150,000; Full time

Benefits offered by this job

Hybrid work schedule

Benefits package

Generous PTO

Job summary

Venerable is seeking a software/ML engineer to join a hybrid Agile team developing data systems, micro-services, web apps, and AI/ML solutions. You will support the full ALM lifecycle—from analysis and design through deployment and ongoing support—collaborating with senior engineers and business stakeholders to deliver robust software.

Day-to-day responsibilities include designing, developing, and deploying ML models on AWS, automating training and deployment workflows, monitoring model

Qualifications

• Bachelor's degree in Computer Science, Data Science, IT, or related field (preferred).
• 1–3+ years of professional experience in AI/ML and enterprise-class SOA/micro-services systems and web-based applications.
• Experience with AWS services: SageMaker, Lambda, EC2, S3, and Redshift.

Responsibilities

• Assist in designing, developing, and deploying machine learning models using AWS services (SageMaker, Lambda, EC2, S3, Redshift).
• Support automated workflows for model training and deployment (AWS Step Functions, Lambda).
• Monitor model performance and suggest adjustments.
• Work across the full ALM lifecycle on system elements (clients, servers, services, middleware, persistence, communication).
• Engage in software configuration management, CI/CD, automated testing, and DevSecOps practices.

Skills

Python

JavaScript

Education

Bachelor's degree in Computer Science, Data Science, IT, or related field

Tools

AWS

Docker

Git/GitHub

CI/CD tools

Job description

Venerable is seeking a software/ML engineer to join a hybrid Agile team developing data systems, micro-services, web apps, and AI/ML solutions. You will support the full ALM lifecycle—from analysis and design through deployment and ongoing support—collaborating with senior engineers and business stakeholders to deliver robust software.

Day-to-day responsibilities include designing, developing, and deploying ML models on AWS, automating training and deployment workflows, monitoring model