AI/ ML Ops Engineer

Primary skill :

1. Hands on Years of relevant experience in Design and implementation of ML Ops solutions on cloud (preferably Azure)
2. Experience with machine learning frameworks such as TensorFlow or PyTorch
3. Expertise in programming languages such as Python or Java
4. Experience in deployment technologies such as Kubernetes or Docker
5. Strong understanding of machine learning algorithms, large language models and statistical modeling.
6. Experience in Azure cloud platform and Azure ML services

Secondary skill :

1. Adapt to emerging trends, tools, and best practices in MLOps specific to large language models, such as new model compression techniques, pipeline automation, and monitoring solutions, to ensure efficient and scalable LLM implementations.
2. Strong analytical and problem-solving skills.
3. Experience in working with Agile methodology.

Role description:

1. Design and implement automated machine learning pipelines for data processing, model training, and deployment.
2. Develop and maintain cloud (Azure) infrastructure for machine learning models in production.
3. Monitor and optimize machine learning models for scalability, performance, and reliability.
4. Implement and manage continuous integration and delivery pipelines for machine learning models.
5. Collaborate with data scientists and ML engineers to ensure smooth integration of models to production environment.
6. Develop and maintain tools for monitoring, logging, and debugging machine learning models.
7. Stay up-to-date with the latest research and technology advancements in the field of machine learning operations.