Machine Learning Engineer

RESPONSIBILITIES:
Kforce has a client that is seeking a Machine Learning Engineer in Los Angeles, CA.

REQUIREMENTS:
* Bachelor's degree in Computer Science, Artificial Intelligence, Informatics or closely related field; Master's degree in computer science, engineering or closely related field preferred
* 3 or more years relevant Machine Learning Engineer Experience
* 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
* Proven experience with: Artificial intelligence and machine learning platforms (e.g., AWS, Azure or Google Cloud Platform); 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). MLOps engineering principles, agile methodologies, and DevOps life-cycle management; Technical writing and documentation for AI/ML models and processes; Healthcare data and machine learning use cases
* Healthcare Expertise: Understanding of healthcare regulations and standards, and familiarity with Electronic Health Records (EHR) systems, including integrating machine learning models with these systems
* 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

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

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