Machine Learning Engineer (Remote)

Irvine Technology Corporation - East Los Angeles, CA

Full-time - Mid Level

Remote - East Los Angeles, CA

Administrative and Support Services

About the position

The Machine Learning Engineer position is a contract role at a prestigious academic medical center, focused on deploying and maintaining production-grade machine learning models. The role requires collaboration with various teams to develop scalable ML infrastructures and optimize deployment frameworks, ensuring compliance with healthcare regulations.

Responsibilities

• Deploy and maintain production-grade machine learning models with real-time inference, scalability, and reliability.
• Develop end-to-end scalable ML infrastructures using cloud platforms like AWS, Google Cloud Platform, or Azure.
• Lead engineering efforts in creating and implementing methods and workflows for ML/GenAI model engineering.
• Develop AI pipelines for data processing needs, including data ingestion, preprocessing, and search and retrieval.
• Collaborate with data scientists, data engineers, analytics teams, and DevOps teams to design robust deployment pipelines.
• Implement and optimize CI/CD pipelines for machine learning models, automating testing and deployment processes.
• Set up monitoring and logging solutions to track model performance and system health.
• Implement version control systems for machine learning models and associated code.
• Ensure machine learning systems meet security and compliance standards.
• Maintain clear and comprehensive documentation of ML Ops processes and configurations.

Requirements

• Bachelor's Degree in computer science, artificial intelligence, informatics, or related field; Master's Degree preferred.
• 3 or more years of relevant Machine Learning Engineer experience.
• Proven experience in deploying and maintaining production-grade machine learning models.
• Proficiency in developing scalable ML infrastructures using cloud platforms.
• Ability to lead engineering efforts in ML/GenAI model engineering and deployment frameworks.
• Experience in developing AI pipelines for data processing needs.
• Demonstrated ability to collaborate with various teams for deployment pipelines.
• Expertise in implementing and optimizing CI/CD pipelines for machine learning models.
• Competence in setting up monitoring and logging solutions for model performance.
• Experience implementing version control systems for machine learning models.
• Knowledge of security and compliance standards for machine learning systems.
• Skill in maintaining documentation of ML Ops processes.

Nice-to-haves

• Healthcare expertise, including understanding of healthcare regulations and EHR systems.
• Proficiency in containerization technologies such as Docker and Kubernetes.

Benefits

• Competitive hourly pay of $58-$68 plus benefits.