Position Overview:
- We are seeking a Machine Learning Engineer to support AI/ML initiatives related to enterprise model development, operational support, and cloud-based machine learning delivery efforts.
- This role will assist in the development, testing, deployment, and maintenance of machine learning solutions supporting both business-as-usual operations and strategic AI programs.
- The ideal candidate will have experience working within Azure environments and supporting machine learning workflows in collaborative engineering teams.
Key Responsibilities:
- Assist in the design, development, and maintenance of AI/ML platform and MLOps infrastructure, supporting deployment, management, and monitoring of ML models, LLMs, and AI driven services.
- Collaborate with data scientists, ML engineers, and software engineers to ensure seamless integration of AI and machine learning capabilities into production applications.
- Support and maintain automated workflows and pipelines for model training, inference, evaluation, retraining, deployment, and monitoring, including prompt based and API driven AI systems.
- Troubleshoot and help resolve issues across models, data pipelines, inference services, and supporting infrastructure.
- Help ensure scalability, security, cost controls, and observability across ML and AI workloads, including monitoring for drift, latency, failures, and compliance with data security and privacy requirements.
- Contribute to and maintain process and operational documentation and stay current on trends and best practices in MLOps, LLMOps, and AI platform operations.
- Support CI/CD processes and deployment workflows using GitHub.
- Build and maintain ML workflows within Databricks environments.
- Utilize Azure AI Foundry and Azure AI services to support model lifecycle activities.
- Assist with document processing and extraction workflows using Azure Document Intelligence.
- Participate in troubleshooting, model validation, testing, and optimization activities.
Required Qualifications:
- 2–4 years of experience in Machine Learning Engineering, Data Engineering, or AI-focused development.
- Experience working within Microsoft Azure environments.
- Strong working proficiency in Python, with applied experience using dynamically typed, object oriented programming patterns.
- Practical experience working across multiple programming languages, such as Python alongside JavaScript, TypeScript, or .NET, in production systems.
- Hands on experience supporting AI/ML platforms, including deployment and operation of ML models and LLM based services.
- Working knowledge of MLOps, LLMOps, and AIOps practices, including monitoring, retraining workflows, and model/prompt lifecycle management.
- Experience implementing or maintaining CI/CD pipelines for ML and AI workloads.
- Familiarity with cloud native architectures, storage, compute, and networking fundamentals.
- Experience with data pipelines, transformations, and performance monitoring.
- Understanding of machine learning model development and deployment concepts.
- Strong analytical and problem-solving skills.
- Ability to work collaboratively within Agile teams.
Required:
- Azure AI Foundry.
- Azure Document Intelligence.
- Databricks.
- GitHub and CI/CD concepts.
Preferred Qualifications:
- Exposure to enterprise AI/ML initiatives.
- Exposure to Palantir or enterprise analytics platforms is a plus.
