Machine Learning Engineer

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

Responsibilities:
* Production Deployment and Model Engineering: Deploying and maintaining production-grade machine learning models, with real-time inference, scalability, and reliability
* Scalable ML Infrastructures: 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: 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: 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: 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: Implementing and optimizing CI/CD pipelines for machine learning models, automating testing and deployment processes
* Monitoring and Logging: Setting up monitoring and logging solutions to track model performance, system health, and anomalies, allowing for timely intervention and proactive maintenance
* Version Control: 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: Maintaining clear and comprehensive documentation of ML Ops processes and configurations

REQUIREMENTS:
* Bachelor's degree Computer Science, Artificial Intelligence, Informatics or closely related field
* Master's degree in Computer Science, Engineering or closely related field preferred
* 3+ years of relevant Machine Learning Engineer experience
* Healthcare Expertise: Understanding of healthcare regulations and standards, and familiarity with Electronic Health Records (EHR) systems, including integrating machine learning models with these systems
* Experience in managing end-to-end ML lifecycle
* Experience in managing automation with Terraform
* Deep understanding of coding, architecture, and deployment processes
* Strong understanding of critical performance metrics
* Extensive experience in predictive modeling, LLMs, and NLP
* 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

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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