Overview
On Site
Contract - W2
Skills
Network
Microsoft Azure
OCI
DevOps
Oracle Machine
Reporting
High Performance Computing
Distributed File System
Reliability Engineering
Linux Administration
Scheduling
Docker
Kubernetes
Collaboration
Computer Science
Data Science
FOCUS
Cloud Computing
Oracle Cloud
Scratch
Linux
Management
Shell Scripting
HPC
GPU
Python
TensorFlow
PyTorch
Machine Learning Operations (ML Ops)
Training
Business Intelligence
Microsoft Power BI
Oracle
Analytics
Computer Networking
Storage
Artificial Intelligence
Machine Learning (ML)
Performance Tuning
Job Details
Position: Lead AI/ML Engineer - On-Prem & Cloud AI Infrastructure
Location: Onsite working in Downtown Brooklyn, NY
Longterm contract
In addition to play the role of a ai/ml engineer, work with my network and devops teams to build out necessary AI/ML infrastructure onprem and cloud. They should know how to do this on their own at a smaller scale and certifications like the following are nice to have:
Azure DevOps Expert
Azure AI Engineer Associate
OCI DevOps Professional
Oracle Machine Learning Specialist
Job Summary:
We are seeking a highly skilled and experienced Senior AI/ML Engineer to lead the development of AI/ML-powered solutions and pilot the adoption AI/ML solutions on Oracle Cloud. This role will also be responsible for architecting an on-premises AI/ML environment, ensuring a robust and scalable MLOps pipeline, and integrating model outputs into business reporting tools such as Power BI, Oracle Analytics, or APIs.
Key Responsibilities:
AI/ML Infrastructure & Deployment
Architect and deploy an on-prem AI/ML environment, including GPU clusters and high-performance computing resources.
Collaborate with infrastructure teams to test and optimize networking storage, and compute resources for AI workloads.
Implement scalable storage solutions (e.g., distributed file systems, object storage) for efficient data handling.
Ensure system reliability, security, and performance through best practices in Linux system administration and resource scheduling.
Configure AI model training and inference environments, leveraging containerization (Docker, Kubernetes) and MLOps pipelines.
Design and implement MLOps processes to support efficient model training, validation, deployment, and monitoring.
Configure and set up ML Oracle Cloud from scratch, ensuring a scalable and production-ready infrastructure.
Collaborate with cross-functional teams to understand data requirements and integrate AI/ML solutions into existing enterprise systems.
Work with developers to integrate AI model outputs into business intelligence tools such as Power BI and Oracle Analytics.
Qualifications:
Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
Certifications in Oracle Data Science Platform preferred.
Required experience:
3+ years of experience in AI/ML engineering with a focus on infrastructure, MLOps, and cloud AI deployment.
Experience configuring and setting up ML platforms on-premises or in Oracle Cloud from scratch.
Strong expertise in Linux-based AI/ML environments, including performance optimization, package management, shell scripting
Experience with HPC environments, GPU clusters (H100, A100, or similar), and distributed AI workloads.
Strong programming skills in Python and experience with AI/ML frameworks such as TensorFlow, PyTorch, or similar.
Hands-on experience with MLOps, including model training, validation, deployment, and monitoring.
Experience integrating AI/ML models into business intelligence tools (Power BI, Oracle Analytics, or APIs).
Experience with high-speed networking, storage solutions, and AI/ML system performance tuning.
Location: Onsite working in Downtown Brooklyn, NY
Longterm contract
In addition to play the role of a ai/ml engineer, work with my network and devops teams to build out necessary AI/ML infrastructure onprem and cloud. They should know how to do this on their own at a smaller scale and certifications like the following are nice to have:
Azure DevOps Expert
Azure AI Engineer Associate
OCI DevOps Professional
Oracle Machine Learning Specialist
Job Summary:
We are seeking a highly skilled and experienced Senior AI/ML Engineer to lead the development of AI/ML-powered solutions and pilot the adoption AI/ML solutions on Oracle Cloud. This role will also be responsible for architecting an on-premises AI/ML environment, ensuring a robust and scalable MLOps pipeline, and integrating model outputs into business reporting tools such as Power BI, Oracle Analytics, or APIs.
Key Responsibilities:
AI/ML Infrastructure & Deployment
Architect and deploy an on-prem AI/ML environment, including GPU clusters and high-performance computing resources.
Collaborate with infrastructure teams to test and optimize networking storage, and compute resources for AI workloads.
Implement scalable storage solutions (e.g., distributed file systems, object storage) for efficient data handling.
Ensure system reliability, security, and performance through best practices in Linux system administration and resource scheduling.
Configure AI model training and inference environments, leveraging containerization (Docker, Kubernetes) and MLOps pipelines.
Design and implement MLOps processes to support efficient model training, validation, deployment, and monitoring.
Configure and set up ML Oracle Cloud from scratch, ensuring a scalable and production-ready infrastructure.
Collaborate with cross-functional teams to understand data requirements and integrate AI/ML solutions into existing enterprise systems.
Work with developers to integrate AI model outputs into business intelligence tools such as Power BI and Oracle Analytics.
Qualifications:
Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
Certifications in Oracle Data Science Platform preferred.
Required experience:
3+ years of experience in AI/ML engineering with a focus on infrastructure, MLOps, and cloud AI deployment.
Experience configuring and setting up ML platforms on-premises or in Oracle Cloud from scratch.
Strong expertise in Linux-based AI/ML environments, including performance optimization, package management, shell scripting
Experience with HPC environments, GPU clusters (H100, A100, or similar), and distributed AI workloads.
Strong programming skills in Python and experience with AI/ML frameworks such as TensorFlow, PyTorch, or similar.
Hands-on experience with MLOps, including model training, validation, deployment, and monitoring.
Experience integrating AI/ML models into business intelligence tools (Power BI, Oracle Analytics, or APIs).
Experience with high-speed networking, storage solutions, and AI/ML system performance tuning.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.