Machine Learning Engineer

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Kforce Technology Staffing, is seeking a Machine Learning Engineer to design and implement comprehensive machine learning workflows and pipelines covering data preparation, model training, deployment, and monitoring. 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) 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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