Machine Learning Engineer

At Stage-X Space, we are transforming how businesses operate through cutting-edge enterprise data solutions. By harnessing the power of Artificial Intelligence, we develop innovative technologies that drive efficiency and growth. Join us in revolutionizing the digital landscape and empowering organizations to succeed through AI-driven advancements.

We are seeking a skilled MLOps Engineer to bridge the gap between machine learning development and production. You will be responsible for building scalable AI pipelines, automating model deployment workflows, and ensuring the long-term reliability of our machine learning systems. This is a collaborative role where you will work closely with Data Scientists and Software Engineers to turn R&D breakthroughs into production-grade solutions.

• Production Integration: Deploy machine learning models into scalable, high-availability production environments.
• Automation (CI/CD): Design and maintain automated CI/CD pipelines for ML (CT - Continuous Training).
• Monitoring: Track model performance and data drift to ensure accuracy and reliability post-deployment.
• Architecture Optimization: Support R&D by optimizing system architectures for performance and cost-efficiency.
• Collaboration: Work across functional teams to align AI/ML applications with business objectives.

• MLOps Expertise: Strong understanding of MLOps principles, including model versioning, orchestration, and lifecycle management.
• Tech Stack: Proficiency in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow).
• Infrastructure: Solid experience with containerization (Docker, Kubernetes) and cloud platforms (AWS, GCP, or Azure).
• Tools: Experience with tools like MLflow, Kubeflow, or DVC is highly preferred.
• Academic Background: Bachelor’s or advanced degree in Computer Science, Engineering, or a related field.
• Soft Skills: Strong problem-solving abilities, project management skills, and a keen attention to detail.

• Ready to shape the future of AI? Please send your resume and a brief cover letter to: 📧 [email protected]