<p>Kforce has a client that is seeking an AI/ML Engineer in Jersey City, NJ.</p> <p>Responsibilities:</p> <ul> <li>AI/ML Engineer will partner with Data Scientists and to help use the foundational platform upon which models can be built and trained </li><li>Operationalize ML Models at scale (e.g. Serve predictions on tens of millions of customers) </li><li>Exploring new technology trends and maximizing them to simplify our data and ML ecosystem </li><li>Designing & developing a feature generation & store framework that promotes sharing of data/features among different ML models </li><li>Build tools to help detect shifts in data/features used by ML models to help identify issues in advance of deteriorating prediction quality, monitoring the uncertainty of model outputs, automating prediction explanation for model diagnostics </li><li>As an AI/ML Engineer, you will drive Innovation and implementing solutions with future thinking </li><li>Guiding teams to improve development agility and productivity </li><li>Resolving technical roadblocks and mitigating potential risks </li><li>Delivering system automation* Bachelor's or Master's degree or equivalent experience in a technology related field (e.g. Computer Science, Engineering, etc.) </li><li>5+ years of proven experience in developing and implementing Python-based cloud applications and/or machine learning solutions </li><li>Solid experience in Agile methodologies (Kanban and Scrum) </li><li>Proven experience in building cloud-native applications using a range of AWS services, including but not limited to SageMaker AI, Bedrock, S3, CloudFormation (CFT), SNS, SQS, Lambda, AWS Batch, Step Functions, EventBridge, and CloudWatch; Familiarity with both Azure Cognitive Services, particularly for deploying OpenAI models, and Google Compute Vertex is beneficial </li><li>Strong experience with CI/CD tools, particularly Jenkins, for automating and streamlining the software development pipeline </li><li>Hands-on experience with containerization technologies such as Docker for building and deploying applications </li><li>Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required </li><li>Strong knowledge of developing highly scalable distributed systems using Open-source technologies </li><li>Expertise in infrastructure as code (IaC) services, including AWS CloudFormation and tools like Terraform or OpenTofu, for managing and provisioning cloud resources </li><li>Proficiency in Python software development with strong experience in its ML ecosystem (NumPy, pandas, sklearn, TensorFlow, etc.), along with solid skills in Linux scripting </li><li>Proficient in using version control systems like Git for effective code management and collaboration </li><li>Ability to design and implement software using both object-oriented and functional programming paradigms </li><li>Basic knowledge of Java and Groovy is a plus </li></ul>