Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer Mandatory Experience: Model Deployment Model Monitoring ML Ops Vertex AI Work Location Frisco, TX (Remote Considered) Job Description: Senior Machine Learning Engineer This position will collaborate closely with stakeholders, including data scientists and analysts, to understand the organization's data and modeling requirements. You will leverage your expertise in programming, MLOps frameworks, and pipeline integration to design scalable architectures that ensure smooth data and model flow. These diligent engineers focus on MLOps reliability and performance, implementing solutions that optimize computing, data retrieval, and model deployment. They work with a variety of tools and technologies such as containerization, automation, and model deployment frameworks, and cloud platforms, to manage model refreshes, automate manual data inputs, and tweak/adapt models with new data sources. The Senior Machine Learning Engineer will act as a technical leader whose purpose is to improve client's overall business performance through deploying Marketing Mix Modeling and Optimization models in real-time and ensuring these models can be run with efficiency and consistency. You will work with Data Engineers and Front-End Designers/Developers to ensure technical business requirements are met. You are expected to be the overall expert in full-stack development of Machine Learning and Applied Science centric products. What you will do: • Define and implement machine learning pipelines to support central data science products • Containerize models and deploy them efficiently in pipelines • Extract data from core systems to solve analytical problems; ensure development teams have the required data • Process complex data sets efficiently, with the lowest compute cost • Develops tools to facilitate data integration, analytics, data cleaning / transformation, and the deployment of ML/AI models • Work closely with database teams on topics related to data requirements, cleanliness, accuracy etc. • Interact with the business divisions to understand all requirements to develop business insights for CRM and translates them into data structures and data model requirements to IT • Track analytics impact on business You will ideally have: • MS/PhD and minimum of 7 years of demonstrated success in deploying full-stack solutions that center around Machine Learning and Applied Science • 5 years of experience in deploying business solutions into production and managing the overall technical excellence of deployments. • Expertise in MLOps frameworks for example containerization (Docker and Kubernetes), Automation (CI/CD), and model deployment (Kubeflow, MLFlow). • Strong problem-solving skills and ability to formulate and solve complex data-related problems. • Expertise in API development • Experience with Machine learning system design • Expertise in Cloud platforms, preferably Google Cloud • Experience in developing applications in high volume data staging/ETL environments • Background in software engineering development including collaboration (source control) and agile • Domain knowledge on marketing and/or Mix Market Models is a plus • Team-player and a Team-first mentality • Possess excellent oral and written communication skills • Highly detail-oriented and organized • Possess strong business and financial acumen