AI-ML Engineer (Gen AI/MLops)

Ccube is a rapidly growing digital technology service provider and a preferred partner for numerous Fortune 500 companies aiming to leverage disruption for competitive advantage through innovative digital strategies.

Ccube leverages its proficiency in transforming customer experiences, data analytics, artificial intelligence, platform and product engineering, cloud infrastructure, and security to assist clients in rapid innovation for expansion, development of digital products, establishment of service platforms, and enhancement of data-driven performance.

Ccube is Hiring AI / ML Engineer's in Multiple Locations. AI-ML Engineer (Gen AI / MLops) Atlanta GA (Onsite Day1. Hybrid 3 Days a Week) Long Term W2 / Full Time Highly Preferred Looking for AI / ML Engineer / with experience in data engineering, feature engineering and MLOps Key Responsibilities : Design and architect scalable AI platforms to develop, deploy AI solutions leveraging ML techniques and Deep Learning Techniques.

Drive Joint Architecture Design to collaborate with business stakeholders, data scientists, engineering teams, product, and other key partners to gather functional, non-functional requirements for solving AI use cases on the AI Platform Evaluate emerging technologies and tools in the AI area and do fitment analysis to the Enterprise AI Platform and capabilities strategy.

Define and implement AI / ML architecture best practices, frameworks, and standards. Lead AI / ML infrastructure setup, including cloud services selection, data pipelines, and model deployment.

Ensure robustness, reliability, and scalability of AI / ML solutions in production environments. Design and implement data governance, security, and compliance measures for AI / ML platforms.

Optimize AI / ML workflows for performance, cost efficiency, and resource utilization. Provide technical leadership and mentorship to AI / ML development teams.

Communicate AI / ML architecture decisions and strategies to stakeholders and executives. Key Requirements : Proven experience as an AI / ML platform Deep understanding of ML algorithms, Deep Learning architechture, models, and frameworks (e.

g., TensorFlow, PyTorch, Scikit-Learn). Expertise in cloud platforms (e.g., GCP, Azure) and their AI services. Strong knowledge of Model development life cycle, software engineering principles, data engineering principles Experience with containerization and orchestration tools onprem and cloud (e.

g., AKS, GKE, OpenShift Container Platform, Docker, Kubernetes) for deploying AI / ML models. Ability to design and optimize distributed computing systems for AI / ML workloads.

Familiarity with DevOps practices, CI / CD pipelines, and automation tools in AI-ML contexts. Excellent problem-solving skills and ability to address complex technical challenges.

Effective communication skills to collaborate with cross-functional teams and stakeholders. Benefits : - Actual compensation is influenced by years of experience, specialized skill sets, and unique qualifications Ccube provides various benefits such as subsidized medical, dental, vision Insurance Powered by JazzHR