Lead Data Scientist

Job Overview: Pay Range: $55hr - $60hr Responsible for designing, implementing, and managing end-to-end MLOps pipelines, machine learning infrastructure, and scalable AI solutions on Google Cloud Platform. Requirement/Must Have: Strong experience with Google Cloud Platform services in the MLOps and machine learning domain. Experience with Vertex AI, Kubeflow, Cloud Storage, and Artifact Registry. Proven ability to design and implement end-to-end machine learning pipelines for data management, model training, and deployment. Hands-on experience with Docker containerization technologies. Familiarity with CI/CD practices and automation pipelines. Knowledge of machine learning frameworks such as TensorFlow. Strong understanding of the machine learning lifecycle and MLOps best practices. Responsibilities: Design, build, and manage automated data ingestion, transformation, and validation pipelines using Kubeflow Pipelines and Vertex AI Pipelines. Implement scalable and reusable feature engineering pipelines for diverse datasets. Containerize feature engineering logic and machine learning workflows. Integrate and manage data validation processes to detect and remediate data quality issues. Utilize AI Agents and Generative Language API capabilities to improve data validation and automation workflows. Set up and maintain continuous training pipelines using Vertex AI Pipelines and Cloud Scheduler. Implement experiment tracking to monitor model parameters, metrics, and artifacts. Configure and execute hyperparameter tuning jobs using Vertex AI Training services. Establish model versioning systems and manage model artifacts in centralized repositories using Cloud Storage. Containerize machine learning models and dependencies using Docker. Manage container images using Artifact Registry. Build and maintain CI/CD workflows for machine learning deployment automation. Configure and manage low-latency production inference environments using Vertex AI Endpoints. Ensure scalable, reliable, and efficient model serving for real-time inference workloads. Should Have: Strong analytical and problem-solving skills. Ability to work with complex machine learning systems and cloud-native architectures. Strong collaboration and communication skills. Experience with Generative Language API, Gemini models, or AI Agent integrations preferred. Skills: Google Cloud Platform (GCP). Vertex AI and Kubeflow Pipelines. Cloud Storage and Artifact Registry. Docker containerization. CI/CD pipeline automation. TensorFlow. Hyperparameter tuning and experiment tracking. Data validation and feature engineering. Model deployment and real-time inference. MLOps and machine learning lifecycle management. Qualification And Education: Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or related field preferred. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.