Recutify Inc. is looking for a Senior Machine Learning Ops Engineer to drive the deployment, scaling, and maintenance of machine learning models within our cutting-edge AI ecosystem. In this remote contract role, you'll optimize pipelines and infrastructure to deliver robust ML solutions for enterprise clients.

Recutify Inc., a leader in AI-driven solutions, is excited to announce an opening for a Senior Machine Learning Ops Engineer. In this pivotal role, you will architect and implement scalable MLOps pipelines to support the end-to-end lifecycle of machine learning models, from development to production deployment. You'll collaborate with data scientists, software engineers, and product teams to ensure reliable, efficient, and cost-effective ML operations.

Key responsibilities include designing automated workflows for model training, validation, and serving; optimizing infrastructure for high availability and performance; implementing robust monitoring and alerting systems to proactively address issues; and contributing to best practices in CI/CD for ML workloads. You'll leverage cloud-native technologies to handle large-scale data processing and inference, while ensuring compliance with security and data privacy standards.

This remote contract position offers the chance to work on transformative projects that impact industries worldwide. If you have a passion for bridging the gap between ML research and production realities, join Recutify Inc. to shape the future of intelligent systems.

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field
• 5+ years of experience in MLOps, DevOps, or Site Reliability Engineering, with a focus on machine learning workflows
• Proficiency in cloud platforms such as AWS, GCP, or Azure, including services like SageMaker, Vertex AI, or Kubernetes
• Strong knowledge of CI/CD pipelines, containerization (Docker), and orchestration tools (Kubernetes, Terraform)
• Experience with ML frameworks like TensorFlow, PyTorch, and model serving technologies (e.g., TensorFlow Serving, KServe)
• Familiarity with monitoring tools (Prometheus, Grafana) and version control (Git)
• Excellent problem-solving skills and ability to work collaboratively in a fast-paced environment
• Strong communication skills for cross-functional teamwork

• Competitive monthly salary with performance incentives
• Fully remote work setup with flexible hours
• Opportunities for professional development and certifications in emerging ML technologies
• Health and wellness benefits, including mental health support
• Generous paid time off and work-life balance initiatives
• Access to cutting-edge tools and resources for innovation
• Collaborative team environment with mentorship opportunities