Machine Learning Engineer

RESPONSIBILITIES:
Kforce has a client in Dublin, OH that is hiring for a Machine Learning Engineer to design and implement comprehensive machine learning workflows and pipelines covering data preparation, model training, deployment, and monitoring.

Key Responsibilities:
* Perform advanced statistical analyses, including both predictive and prescriptive modeling techniques
* Develop robust monitoring systems to track model performance and system health, and respond promptly to production outages
* Partner closely with product teams to lead API development, maintain ML infrastructure, and integrate machine learning capabilities into products seamlessly
* Collaborate with data engineers to build and refine data pipelines, packages, and tools essential to the data science team's operations
* Provide technical and programmatic support throughout the full project lifecycle-from concept development and system definition to acquisition planning, design, integration, testing, delivery, and deployment
* Engineer scalable, production-ready solutions for managing and serving machine learning models and data science applications
* Create and maintain documentation and technical materials, including evaluation plans, Confluence pages, white papers, presentations, test reports, technical manuals, formal recommendations, and project summaries

REQUIREMENTS:
* Master's degree in Computer Science, Engineering, Applied Statistics or related field, or Bachelor's degree in Computer Science, Engineering, Applied Statistics or related field and 2 years of experience in machine learning, or 4 years of experience in machine learning
* Excellent communication skills including written, verbal, and technology diagrams
* Understanding of the model development lifecycle and has had exposure to DevOps/MLOps/LLMOps/ModelOps
* Experience with enterprise Cloud ML Services (i.e., Sagemaker, AzureML, Vertex AI), and open source AI/ML frameworks
* Strong analytical and problem-solving skills
* Ability to work both independently and in a team environment
* Strong organizational, planning & problem-solving skills

Preferred:
* Azure certification or AWS certification
* Exposure in continuous integration & delivery (CI/CD) practices and tools (Git, Jenkins, uDeploy)
* Exposure in with building container-based systems such as Docker
* Exposure in relational and dimensional data modeling techniques
* Exposure in machine learning models and concepts: regression, random forest, boosting, NLP, and deep learning
* Exposure in developing and deploying complex and scalable software systems in the analytics space
* Exposure in Azure Data Lake or other cloud data warehousing solutions
* Exposure in triaging, troubleshooting, and fixing issues in Production environments
* Exposure with orchestration and scheduling tools (Control-M)

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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