Requirements
Requirements: Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field. 3+ years of experience in machine learning or AI solutions development, preferably using Google Cloud Platform. Proficient in programming languages such as Python or R, with a strong understanding of machine learning libraries (e.g., TensorFlow, scikit-learn). Experience with cloud-based AI technologies, especially GCP services like Vision AI, Natural Language API, and AutoML. Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques. Ability to work with large datasets, utilizing BigQuery or similar data processing tools. Excellent problem-solving skills and a strong analytical mindset. Capable of communicating complex technical concepts to diverse audiences effectively. Preferred Qualifications: Google Cloud certifications (e.g., Google Cloud Professional Data Engineer or Google Cloud Professional Machine Learning Engineer) are a plus. Experience with MLOps practices and tools for model deployment and management. Familiarity with DevOps practices as they relate to AI and machine learning. A background in statistics or applied mathematics is desirable.
Description
Müller’s Solutions is excited to announce an opening for a Google Cloud AI Specialist to drive our artificial intelligence initiatives leveraging Google Cloud Platform (GCP). In this role, you will be responsible for designing and implementing AI and machine learning solutions to help transform our data into actionable insights and enhance decision-making processes across the organization. Key Responsibilities:Develop and deploy machine learning models using GCP tools such as AI Platform, TensorFlow, and AutoML.Collaborate with cross-functional teams to identify business needs and translate them into AI and ML project requirements.Conduct data analysis to prepare datasets for model training and evaluation while ensuring data quality and integrity.Implement and optimize AI workflows that facilitate real-time data processing and inference.Stay updated on the latest advancements in AI and machine learning technologies to continuously improve our offerings.Provide technical guidance and support to teams on best practices for using Google Cloud AI services.Document AI project implementations, model performance evaluations, and ongoing maintenance procedures.Contribute to developing educational materials and training sessions on AI capabilities for staff and stakeholders.Monitor and assess the performance of deployed AI models, making adjustments as necessary to ensure effectiveness.