2 Lead AI Engineer Machine Learning Operations Mlops jobs in whatjobs
Lead AI Engineer - Machine Learning Operations (MLOps)
Posted 11 days ago
Job Viewed
Job Description
Our client is at the cutting edge of AI and Emerging Technologies, and they are seeking a highly skilled Lead AI Engineer to spearhead their Machine Learning Operations (MLOps) initiatives. This role is pivotal in bridging the gap between model development and production deployment, ensuring the scalability, reliability, and efficiency of our AI systems. You will be responsible for designing, building, and maintaining the infrastructure and pipelines that support the end-to-end lifecycle of machine learning models. This includes data pipelines, model training, versioning, deployment, monitoring, and continuous integration/continuous deployment (CI/CD) for ML. As a Lead Engineer, you will also mentor junior engineers and guide architectural decisions.
Responsibilities:
Qualifications:
Responsibilities:
- Design, implement, and manage robust MLOps pipelines for automated model training, validation, and deployment.
- Develop and maintain infrastructure for scalable machine learning model serving.
- Implement strategies for monitoring model performance, drift detection, and triggering retraining.
- Collaborate with data scientists and software engineers to integrate ML models into production systems.
- Set up and manage CI/CD pipelines tailored for machine learning workflows.
- Ensure the security, scalability, and reliability of AI/ML infrastructure.
- Evaluate and integrate new MLOps tools and technologies.
- Provide technical leadership and mentorship to a team of AI/ML engineers.
- Document MLOps processes and best practices.
Qualifications:
- Master's or Ph.D. in Computer Science, Engineering, or a related quantitative field.
- 5+ years of experience in software engineering, with a significant focus on MLOps or productionizing machine learning models.
- Proficiency in cloud platforms (AWS, Azure, GCP) and their ML services.
- Strong experience with containerization technologies (Docker, Kubernetes).
- Expertise in CI/CD tools (Jenkins, GitLab CI, GitHub Actions) and infrastructure-as-code (Terraform, Ansible).
- Solid understanding of machine learning frameworks (TensorFlow, PyTorch, scikit-learn) and model development lifecycle.
- Excellent programming skills in Python.
- Strong problem-solving abilities and a proactive approach to identifying and resolving issues.
- Leadership experience and the ability to mentor and guide technical teams.
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Lead AI Engineer - Machine Learning Operations (MLOps)
Posted 6 days ago
Job Viewed
Job Description
Our client is seeking an accomplished Lead AI Engineer specializing in Machine Learning Operations (MLOps) to join their dynamic, fully remote team. This role is critical for bridging the gap between AI research and production deployment, ensuring the seamless integration and scalability of machine learning models. You will be instrumental in designing, building, and maintaining the infrastructure and workflows required for efficient ML model development, deployment, monitoring, and retraining. Responsibilities include developing CI/CD pipelines for machine learning, automating model testing and validation, and implementing robust monitoring solutions to track model performance and detect drift. You will work closely with data scientists and software engineers to optimize ML models for production environments, ensuring reliability, scalability, and performance. The ideal candidate will possess a strong background in software engineering and a deep understanding of machine learning principles and lifecycles. A Master's or Ph.D. in Computer Science, AI, or a related quantitative field, combined with at least 6 years of relevant industry experience, is required. Proven experience with MLOps best practices, cloud platforms (AWS, Azure, GCP), containerization technologies (Docker, Kubernetes), and infrastructure as code tools (Terraform) is essential. Proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn are also necessary. You should have hands-on experience with MLOps platforms and tools such as MLflow, Kubeflow, or SageMaker. Excellent problem-solving, communication, and collaboration skills are vital for success in this remote, team-oriented role. Join us in driving AI innovation from **Mombasa, Mombasa, KE**.
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