RIT Solutions, Inc.
Role: Senior Data Scientist
Duration: 12 months
Location: Phoenix Arizona will get first preference, Remote is ok
Time zone: PST Time zone
Role Requirements:
8+ years of experience in Machine learning engineering /MLE , data science and data engineering, with a proven track record of delivering impactful solutions. Proven experience in AI Application & Infrastructure Optimization in terms of Capacity, Performance and Cost rchitectural Optimization
- Experience in optimization of solution architectures with a focus on data security, privacy, application reliability, infrastructure scalability, and cost-efficiency for Data Science and Generative AI platforms. Scalable AI Solution Deployment
- Experience in designing and implementing scalable AI and Data Science solutions capable of handling large-scale, distributed data and compute workloads across hybrid and cloud-native environments(OCI). Performance Tuning for AI/ML and GenAI Workloads
- Experience in hyperparameter tuning and performance optimization for AI/ML and Generative AI models to maximize accuracy, efficiency, and resource utilization. I Lifecycle Management
- Experience in robust AI pipelines for model versioning, testing, validation, and deployment, ensuring seamless integration into production environments with CI/CD best practices. I Full stack : Experience in in any full stack /development
experience in Java, or .Net or React, Node.js, Flask/Django, REST APIs. Proficiency in Python, SQL, and machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch. Experience in EDA, data engineering, creating data pipelines and processing huge volume of data. Understanding of cloud platforms (OCI, Azure) and containerization (Docker, Kubernetes). Excellent problem-solving, communication, and stakeholder management skills. Prior experience in a customer-facing or product-oriented role. Master's in computer science, Machine Learning , Data Science, Statistics, or a related field.
Role Requirements:
8+ years of experience in Machine learning engineering /MLE , data science and data engineering, with a proven track record of delivering impactful solutions. Proven experience in AI Application & Infrastructure Optimization in terms of Capacity, Performance and Cost rchitectural Optimization
- Experience in optimization of solution architectures with a focus on data security, privacy, application reliability, infrastructure scalability, and cost-efficiency for Data Science and Generative AI platforms. Scalable AI Solution Deployment
- Experience in designing and implementing scalable AI and Data Science solutions capable of handling large-scale, distributed data and compute workloads across hybrid and cloud-native environments(OCI). Performance Tuning for AI/ML and GenAI Workloads
- Experience in hyperparameter tuning and performance optimization for AI/ML and Generative AI models to maximize accuracy, efficiency, and resource utilization. I Lifecycle Management
- Experience in robust AI pipelines for model versioning, testing, validation, and deployment, ensuring seamless integration into production environments with CI/CD best practices. I Full stack : Experience in in any full stack /development
experience in Java, or .Net or React, Node.js, Flask/Django, REST APIs. Proficiency in Python, SQL, and machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch. Experience in EDA, data engineering, creating data pipelines and processing huge volume of data. Understanding of cloud platforms (OCI, Azure) and containerization (Docker, Kubernetes). Excellent problem-solving, communication, and stakeholder management skills. Prior experience in a customer-facing or product-oriented role. Master's in computer science, Machine Learning , Data Science, Statistics, or a related field.