We are seeking an MLOps Engineer experienced in managing, scaling, and deploying machine learning models in a distributed environment. You will work alongside a diverse, globally distributed team to develop ground-breaking solutions that optimize Large Language Models (LLMs) to function in a local cluster environment. Your role will be integral in realizing our ambitious vision of optimizing and scaling AI at the edge.
- Develop, manage, and optimize ML models lifecycle in production using the Turing Pi platform and Nvidia CUDA.
- Implement continuous integration and deployment systems for ML workflows.
- Monitor ML models in production, identify issues and inefficiencies, and propose solutions.
- Design and implement MLOps tools and frameworks to improve the automation and efficiency.
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field.
- Proven experience in MLOps, DevOps, DataOps, or similar roles.
- Strong understanding of Machine Learning algorithms and principles.
- Experience with containerization technologies (Docker, Kubernetes) and cloud platforms.
- Proficiency in Python
- Proficiency in CUDA
- Experience with data pipeline and workflow management tools (Kubeflow, Argo, etc.).
- Exceptional problem-solving skills, attention to detail, and strong analytical abilities.
- Excellent communication and teamwork skills.
- Knowledge of or experience with the Turing Pi platform.
- Familiarity with open Large Language models (Llama, Falcon, etc.).
- Familiarity with ML frameworks (TensorFlow, PyTorch, etc.).
Turing Pi is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
If you are passionate about shaping the future of distributed AI systems and microservices, we would love to hear from you. Apply today to join our innovative team!
How to Apply
Interested applicants should submit their resume and a brief statement of interest via our job posting portal.