Healthcare Machine Learning Engineer- Cerner

Healthcare Machine Learning Engineer Opportunity!!

This Jobot Job is hosted by: Robert Reyes
Are you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume.
Salary: $160,000 - $176,000 per year

A bit about us:

Prestige Hospital System
Placed #1 in both California in a broad assessment of excellence in hospital-based patient care.

Why join us?

Competitive Salary$$
Stellar Benefits (Medical, Dental Vision, Life Insurance)
Flexible Schedule
Job Stability
Career growth
The position offers a competitive salary
If you are passionate, thrive in a fast-paced environment and are ready to take your career to the next level, we would love to hear from you.

Job Details

Job Details:

Join our dynamic team as a Permanent Healthcare Machine Learning Engineer at Cerner in the Tech Services industry. This is an exciting opportunity to apply your machine learning skills to transform healthcare and improve patient outcomes. You will be working with cutting-edge technologies, large datasets, and advanced analytics to develop predictive models and algorithms that will revolutionize the way healthcare is delivered. This role requires a deep understanding of machine learning techniques and algorithms, as well as strong coding skills.

Requirements:
3 or more years relevant Machine Learning Engineer Experience
Bachelor's Degree computer science, artificial intelligence, informatics or closely related field
Masters preferred
Healthcare Expertise: Understanding of healthcare regulations and standards, and familiarity with Electronic Health Records (EHR) systems, including integrating machine learning models with these systems.

Job Description:

Production Deployment and Model Engineering: Proven experience in deploying and maintaining production-grade machine learning models, with real-time inference, scalability, and reliability.
Scalable ML Infrastructures: Proficiency in developing end-to-end scalable ML infrastructures using on-premise cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (Google Cloud Platform), or Azure.
Engineering Leadership: Ability to lead engineering efforts in creating and implementing methods and workflows for ML/GenAI model engineering, LLM advancements, and optimizing deployment frameworks while aligning with business strategic directions.
AI Pipeline Development: Experience in developing AI pipelines for various data processing needs, including data ingestion, preprocessing, and search and retrieval, ensuring solutions meet all technical and business requirements.
Collaboration: Demonstrated ability to collaborate with data scientists, data engineers, analytics teams, and DevOps teams to design and implement robust deployment pipelines for continuous improvement of machine learning models.
Continuous Integration/Continuous Deployment (CI/CD) Pipelines: Expertise in implementing and optimizing CI/CD pipelines for machine learning models, automating testing and deployment processes.
Monitoring and Logging: Competence in setting up monitoring and logging solutions to track model performance, system health, and anomalies, allowing for timely intervention and proactive maintenance.
Version Control: Experience implementing version control systems for machine learning models and associated code to track changes and facilitate collaboration.
Security and Compliance: Knowledge of ensuring machine learning systems meet security and compliance standards, including data protection and privacy regulations.
Documentation: Skill in maintaining clear and comprehensive documentation of ML Ops processes and configurations.

Preferred:

Proficiency in Containerization Technologies: Experience with Docker, Kubernetes, or similar tools.
Certification(s) in Machine Learning a plus

Additional REQUIRED qualifications:

Experience in managing end-to-end ML lifecycle.
Experience in managing automation with Terraform.
Containerization technologies (e.g., Docker) or container orchestration platforms (e.g., Kubernetes).
CI/CD tools (e.g., Github Actions).
Programming languages and frameworks (e.g., Python, R, SQL).
Deep understanding of coding, architecture, and deployment processes
Strong understanding of critical performance metrics.
Extensive experience in predictive modeling, LLMs, and NLP
Exhibit the ability to effectively articulate the advantages and applications of the RAG framework with LLMs

If you are a forward-thinking, innovative individual with a passion for healthcare and technology, we would love to hear from you. Become a part of our team and help us transform the future of healthcare!

Interested in hearing more? Easy Apply now by clicking the "Apply Now" button.

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