Senior Systems Engineer - Production AI

SGS Consulting; Boston (MA); On-site; USD 130,000 - 180,000; Full time

Job summary

SGS Consulting is seeking a seasoned AI/ML Engineer to design, deploy, and operate production-grade AI/ML systems and data pipelines in an agile setting. You will build robust CI/CD pipelines with GitHub Actions and deploy software on Kubernetes using GitOps tooling like ArgoCD.

The role emphasizes deploying predictive models in production, ensuring reliability, scalability, and observability while collaborating with scientists and researchers to translate needs into practical digital solutions.

Qualifications

• Bachelor's degree in a related field is required or valued.
• Experience deploying ML models to production systems is essential.
• Strong track record with CI/CD and cloud-based ML pipelines preferred.
• Familiarity with GitHub Actions, Kubernetes, and GitOps tooling is expected.

Responsibilities

• Design, develop, deploy, and operate production-grade AI/ML systems and data pipelines in an agile environment.
• Build, maintain, and optimize CI/CD pipelines using GitHub Actions to enable automated testing and deployment.
• Deploy and operate applications on Kubernetes using GitOps practices (e.g., ArgoCD).
• Develop user-facing applications through APIs and/or graphical interfaces.
• Deploy predictive models into production environments focusing on reliability, scalability, and observability.
• Build and optimize compute pipelines supporting data processing and model training.
• Collaborate with data scientists and researchers to translate scientific needs into digital solutions.
• Participate in agile ceremonies and contribute to continuous improvement of team practices.
• Ensure high standards for code quality, documentation, and knowledge transfer.
• Communicate complex technical concepts clearly to technical and non-technical stakeholders.

Skills

GitHub Actions

Kubernetes

ArgoCD

Python

API development

MLOps

Cloud platforms

Education

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

Job description

Job Responsibilities

• Design, develop, deploy, and operate production grade AI/ML systems and data pipelines in an agile environment.


• Build, maintain, and optimize CI/CD pipelines using GitHub Actions to enable automated testing and deployment.


• Deploy and operate applications on Kubernetes using GitOps practices (e.g., ArgoCD).


• Develop user facing applications through APIs and/or graphical interfaces.


• Deploy predictive models into production environments with a strong focus on reliability, scalability, and observability.


• Build and optimize compute pipelines supporting data processing and model training.


• Collaborate closely with data scientists, computational biologists, and vaccine researchers to translate scientific needs into robust digital solutions.


• Actively participate in agile ceremonies and contribute to continuous improvement of team practices.


• Ensure high standards for code quality, documentation, and knowledge transfer.


• Communicate complex technical concepts clearly to both technical and non technical stakeholders.

Skills

• GitHub Actions and CI/CD pipeline implementation.


• Kubernetes based container orchestration.


• GitOps practices (ArgoCD or equivalent).


• Strong Python programming skills.


• API and/or web application development.


• Production deployment of machine learning models and MLOps practices.


• Familiarity with major cloud platforms (AWS, Azure, or GCP).

Education / Experience

Bachelor's degree or higher in Computer Science, Software Engineering, Data Science, or a related field. Advanced degrees are valued but not required.