Responsibilities
- Build, deploy, and refine machine learning models for practical business applications and customer-facing systems.
- Collaborate with data scientists to transition predictive models into production environments with scalability and maintainability.
- Create and manage data workflows that support model training, inference, and end-to-end lifecycle management.
- Handle large and complex datasets, ensuring data integrity, reproducibility, and consistent version tracking across ML processes.
- Establish monitoring, logging, and alerting systems to evaluate model performance, identify data or concept drift, and trigger retraining.
- Utilize cloud infrastructure (AWS, Azure, GCP) to develop scalable machine learning solutions through managed services and infrastructure-as-code methods.
- Produce clean, modular, and well-documented code that follows MLOps and software engineering standards.
- Keep up with advancements in machine learning tools, frameworks, and industry practices to improve platform capabilities.
Compensation
Base salary is one part of the total compensation. Additional elements may include an annual cash bonus and a full benefits package covering medical, dental, vision, life insurance, and 401(k).
Work Arrangement
Remote (Worldwide)
Other
- This is an exempt position.
- Minimal travel may be required for the right candidate.
- The job title may be adjusted based on the selected candidate’s qualifications and background.
- Base pay is only one part of the total compensation package.