Machine Learning Engineer II

About the role

Job Title: Machine Learning Engineer II

Location: Remote (Local Austin, TX candidates preferred for monthly/quarterly onsite collaboration)

Schedule: Standard Business Hours

Duration: Permanent

Compensation:

$87,740 to $131,610 per year annual salary. Exact compensation may vary based on several factors, including skills, experience, and education. Benefit packages for this role may include healthcare insurance offerings and paid leave as provided by applicable law.

Position Summary

Insight Global is seeking a Machine Learning Engineer II for a leading healthcare organization focused on advancing data-driven innovation. This individual will help build and scale a growing machine learning ecosystem, supporting the deployment, automation, governance, and monitoring of machine learning models in production environments.

Key Responsibilities

Develop and refine machine learning deployment pipelines and workflows for production environments.

Support lifecycle governance, versioning, and reproducibility of ML models.

Implement and maintain model monitoring, performance tracking, and drift detection systems.

Build dashboards and alerting mechanisms for model performance visibility.

Partner with data scientists, software engineers, and DevOps teams on machine learning solutions.

Automate model retraining, validation, and deployment processes.

Apply healthcare data governance and security standards to ML systems.

Optimize and scale cloud infrastructure supporting machine learning workloads.

Create technical documentation and contribute to best practices and knowledge sharing.

Support a greenfield machine learning environment and help establish foundational ML operational processes.

Required Qualifications

4 to 5 years of hands-on AI/ML experience.

Background in software development, data engineering, data analytics, or a related technical discipline.

Strong coding and programming experience.

Experience supporting machine learning models in production environments.

Knowledge of MLOps practices, ML lifecycle management, deployment, monitoring, and automation.

Experience with cloud platforms and ML infrastructure optimization.

Familiarity with CI/CD pipelines, containerization, and cloud infrastructure.

Experience working in enterprise-level data environments.

Exposure to GitHub and Azure Fabric environments.

Bachelor’s degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience).

Preferred Qualifications

Healthcare industry experience.

Experience in regulated environments.

Azure, AWS, or GCP certifications.

Machine Learning or DevOps certifications.

Experience with VS Code.

Prior MLOps, DevOps, or ML Engineering experience.

Equal Employment Opportunity / Accommodation Statement

Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HumanResources@insightglobal.com.