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# Sr. Software Engineer - ML Systems

- **Company:** TALENTHOP LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $153,000.0 - $179,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Unit Testing, Continuous Integration, Data as a Services, Data Validation, Python (Programming Language), PostgreSQL, Machine Learning, NoSQL, Redis, Azure Machine Learning, Software Engineering, SQL Databases, Workflow Management Systems, Pytorch, Snowflake, Kubernetes, Information Technology, Data Management, Machine Learning Operations, Terraform, Databricks
- **Published:** September 25, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pmw05o2xhy

## About the Role

* Bachelor's or Master's degree in Computer Science, Software Engineering, or related field.
 * 7+ years of software engineering experience with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar).
 * Experience with unit and integration testing for ML models including data validation and reproducibility.
 * Familiarity with CI/CD and orchestration tools (Airflow, MLflow, Kubernetes, Terraform) and ML/data platforms (SageMaker, Databricks, Unity Catalog, Snowflake/Snowpark).
 * Strong collaboration skills to work with ML scientists, engineers, and regulatory teams.
 * Ability to operate in ambiguous situations and clarify requirements across stakeholders.

## Description

The Sr. Software Engineer - ML Systems role is responsible for designing, building, deploying, and optimizing production-ready machine learning services within a regulated healthcare environment. The position contributes by ensuring the reliability, performance, and compliance of AI/ML systems that support the organization''s mission to enhance heart disease diagnosis and prevention., * Design, build, and deploy scalable AI/ML services balancing performance, security, and maintainability.

 * Manage full lifecycle delivery of complex features from architecture to post-release monitoring.
 * Define and enforce testing protocols ensuring production reliability and regulatory compliance.
 * Implement CI/CD and MLOps practices for automated model building, testing, and deployment.
 * Translate product requirements into detailed technical designs.
 * Contribute to technical documentation required for regulatory submissions.
 * Collaborate cross-functionally to reduce knowledge silos and ensure system continuity.


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