We are seeking an experienced Senior AI/ML Engineer to join our team as an AI/ML Architect. The ideal candidate will have a deep understanding of advanced machine learning algorithms, cloud-based services, and MLOps practices. They will work on designing, developing, and deploying end-to-end machine learning solutions, particularly in predictive maintenance. This role requires hands-on experience in Azure's ecosystem, data engineering, and scalable AI/ML models.
Key Responsibilities
- Lead the design and development of AI/ML models using advanced machine learning techniques.
- Implement predictive maintenance solutions and deploy them into production environments.
- Develop, train, and fine-tune ML models using deep learning frameworks such as TensorFlow, Keras, and PyTorch.
- Collaborate with data engineers to design and optimize scalable data pipelines for machine learning workflows.
- Utilize Azure Machine Learning and other services within the Azure Ecosystem (Azure Synapse Analytics, Data Factory, Data Lake Storage) for model deployment and data management.
- Perform hyperparameter tuning, model evaluation, and continuous monitoring of machine learning models.
- Employ MLOps practices for automation, including setting up automated machine learning pipelines using Azure DevOps, Docker, and Kubernetes.
- Ensure the seamless integration of machine learning models with existing infrastructure and applications.
- Monitor and maintain the performance of AI/ML models in production, making continuous improvements as needed.
Skills and Experience
- Machine Learning & AI. Expertise in advanced ML algorithms, model evaluation, and deep learning frameworks like TensorFlow, PyTorch, and Keras.
- Programming. Strong proficiency in Python and SQL, with a solid understanding of machine learning libraries such as Scikit-learn.
- Azure Ecosystem. Hands-on experience with Azure ML, Azure Synapse Analytics, Azure Data Factory, Azure SQL Data Warehouse, and Azure Data Lake Storage.
- Big Data & Data Engineering (Good to have). Experience with Spark, Hadoop, Kafka, and designing scalable ETL pipelines.
- MLOps & Automation. Knowledge of MLOps practices, experience with automated machine learning pipelines, and tools like Azure DevOps, Docker, and Kubernetes.
- Proven experience in deploying end-to-end predictive maintenance solutions into production.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
- 5+ years of experience in AI/ML engineering, with a focus on cloud platforms like Azure.
- Experience in deploying large-scale AI/ML models into production environments.
- Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
Why Join Us?
- Work on cutting-edge AI/ML projects in the growing field of predictive maintenance.
- Collaborate with a dynamic and talented team in a highly innovative space.
- Opportunity to lead AI/ML initiatives and shape the future of AI/ML deployment within our organization.