Company
Cox Communications, Inc.Job Family Group
Job Profile
Management Level
Flexible Work Option
Travel %
Work Shift
Compensation
Compensation includes a base salary of $99,000.00 - $165,000.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate’s knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.Job Description
At RapidScale, exceptional technology is powered by exceptional people. As a growing leader in secure, reliable managed cloud solutions, we help SMBs and enterprises alike simplify IT and unleash innovation. With a broad portfolio spanning AWS, Azure and Google to a full set of Private Cloud and Cybersecurity solutions, RapidScale helps companies turn technology into their biggest competitive advantage. As part of the Cox family of companies, we offer best-in-class benefits, a commitment to work-life balance, and an award-winning workplace experience.
We are seeking a highly skilled Senior AI/ML Cloud Engineer to join our innovative team. In this role, you will be responsible for designing, developing, and implementing cutting-edge AI solutions across multiple cloud platforms. You will work on projects that leverage advanced machine learning, deep learning, and large language models to solve complex business problems.
As an Senior AI/ML Cloud Engineer, you will:
Design and develop AI and machine learning solutions using cloud-based managed AI services.
Implement and manage robust monitoring systems for AI/ML models in production environments, ensuring continuous performance tracking, anomaly detection, and model drift analysis; collaborate with cross-functional teams to deploy model updates, maintain version control, and optimize model efficiency over time.
Containerize AI applications and deploy them using cloud orchestration services.
Collaborate with data engineers and data scientists to build end-to-end AI pipelines.
Implement MLOps practices to streamline the development, deployment, and monitoring of AI models.
Use Infrastructure as Code (IaC) to manage and version cloud resources for AI projects.
Ensure clear and accessible knowledge transfer to internal teams and create knowledge-sharing resources to ensure smooth transitions during model handoffs and system updates.
Stay up-to-date with the latest advancements in AI and machine learning technologies.
Contribute to the development of best practices and standards for AI engineering within the organization.
Qualifications
Minimum Requirements
Bachelor’s degree in a related discipline and 4 years’ experience in Cloud Engineering OR a Master’s degree and 2 years’ experience OR a Ph.D. and up to 1 year of experience OR 8 years’ experience in Cloud Engineering.
Experience with Python programming language. Experience with transforming legacy code (e.g., Java, .Net) into cloud-native microservices.
2 years of experience of managing AI services within one cloud platform (e.g. GCP, Azure, AWS).
Experience with container services and orchestration (e.g. GKE, EKS, AKS, ECS, etc.)
Experience in common machine learning, deep learning, and LLM frameworks, such as TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers, LangChain, LangGraph.
Experience with Terraform for Infrastructure as Code (IaC).
Preferred Qualifications
Experience in a client-facing role.
In-depth knowledge of data services across major cloud platforms (e.g. GCP, AWS, Azure).
Professional certifications focus on AI/ML from GCP, AWS, and/or Azure.
Experience with real-time machine learning and streaming data processing.
Benefits
About Us
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