ML/AI Engineer

Job Title: ML/AI Engineer
Tax Term: W2/1099 Only
Location: Fully Remote
Employment Type: Contract

About us

Conglomerate IT is a certified and a pioneer in providing premium end-to-end Global Workforce Solutions and IT Services to diverse clients across various domains. Visit us at

Our mission is to establish global cross culture human connections that further the careers of our employees and strengthen the businesses of our clients. We are driven to use the power of global network to connect business with the right people without bias. We provide Global Workforce Solutions with affability.

We are seeking a skilled ML/AI Engineer with hands-on expertise in AI/ML engineering model implementation and cloud-based solutions. The ideal candidate will have strong experience with Lumenova AI or FiddlerAI for explainable AI and model monitoring coupled with the ability to implement end-to-end AI/ML use cases in a production environment.

• Design develop and deploy AI/ML models to address business use cases.

• Implement model explainability monitoring and governance using Lumenova AI or FiddlerAI.

• Collaborate with data scientists engineers and business teams to integrate AI/ML solutions into production workflows.

• Optimize ML pipelines for scalability reliability and performance in Azure/cloud environments.

• Ensure AI models meet compliance ethical and operational standards.

• Continuously evaluate emerging ML/AI technologies to enhance solution capabilities.

1. Lumenova AI or FiddlerAI Proven experience implementing and managing AI explainability solutions.

2. AI/ML Engineering Expertise Strong background in designing developing and deploying ML models in real-world scenarios.

3. AI Use Case Implementation End-to-end experience translating business problems into AI/ML solutions.

4. Azure/Cloud Knowledge Proficiency in leveraging Azure or other cloud platforms for ML/AI development and deployment.

• Experience with Python TensorFlow PyTorch MLflow or similar ML frameworks.

• Knowledge of MLOps practices (CI/CD for ML monitoring retraining).

• Understanding of data engineering concepts (ETL data pipelines feature stores).

• Strong problem-solving analytical and communication skills.

• Bachelors or Masters degree in Computer Science Data Science Artificial Intelligence or a related field.