Overview
On Site
Full Time
Part Time
Accepts corp to corp applications
Contract - Independent
Contract - W2
Skills
Employment Authorization
Prototyping
Management
Kubernetes
Artificial Intelligence
Microsoft Azure
Machine Learning (ML)
Docker
Cloud Computing
Training
Generative Artificial Intelligence (AI)
Python
SQL
Linux
Machine Learning Operations (ML Ops)
Continuous Integration
Continuous Delivery
Problem Solving
Conflict Resolution
Collaboration
Computer Science
Electronic Engineering
Data Science
Job Details
Hiring: W2 Candidates Only
Visa: Open to any visa type with valid work authorization in the USA
Responsibilities
- Design and implement scalable, cloud-native ML pipelines for production AI solutions.
- Collaborate with data scientists to operationalize ML models from prototypes to production.
- Manage deployment of ML models using Azure Machine Learning and AKS.
- Develop, containerize, and orchestrate services using Docker and Kubernetes.
- Optimize cloud data and compute architectures to ensure cost-effective and reliable deployments.
- Implement robust monitoring, logging, and CI/CD practices to support AI operations (MLOps).
- Work closely with enterprise cloud architects to align AI solutions with client s infrastructure standards.
- Contribute to the evolution of the best practices around AI/ML systems in production environments.
Qualifications
- Minimum 6 years of experience as a Data Scientist, with at least 3 years focused on machine learning engineering in cloud environments.
- Proven experience deploying ML models in Azure, preferably with Azure Machine Learning, Docker, and AKS.
- Hands-on experience building cloud-native pipelines for model training, scoring, and monitoring.
- Familiarity with GenAI concepts and tools (experience operationalizing GenAI is a plus).
- Proficiency in Python, SQL, and Linux-based development environments.
- Strong understanding of MLOps principles, CI/CD pipelines, and production-grade APIs.
- Effective communicator with strong problem-solving skills and ability to work across teams.
Education
- Bachelor s degree in Computer Science, Electronic Engineering, Data Science, or a related field.
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