The Data Sherpas is a cutting-edge team focused on delivering innovative AI and machine learning solutions on Google Cloud Platform (GCP). The Google Cloud AI Engineer will design, develop, and deploy AI/ML models to tackle complex business challenges, collaborating with data scientists, software engineers, and business stakeholders.
Responsibilities:
- Design and implement AI/ML models using Google Cloud services such as Vertex AI, BigQuery ML, AI Platform, and AutoML
- Develop and deploy scalable machine learning models using TensorFlow, PyTorch, and other AI frameworks
- Build and optimize data pipelines using Cloud Dataflow, Cloud Pub/Sub, and Cloud Storage to support AI/ML workflows
- Ensure AI solutions are efficient, scalable, and reliable in a production environment
- Design and implement machine learning training pipelines on GCP
- Optimize model performance through hyperparameter tuning and algorithm selection
- Monitor model accuracy and retrain models as needed to maintain performance
- Work with structured and unstructured data to create datasets for training and evaluation
- Automate data ingestion and preprocessing using tools like BigQuery and Dataflow
- Ensure data quality and integrity for AI/ML workflows
- Implement CI/CD pipelines for AI/ML models using Cloud Build and Vertex AI Pipelines
- Deploy machine learning models using Vertex AI Endpoints and monitor performance in real-time
- Ensure model governance, versioning, and auditing processes are followed
- Collaborate with business stakeholders to identify AI opportunities and translate them into technical solutions
- Evaluate new AI and ML technologies on GCP to improve existing solutions
- Provide technical guidance and thought leadership on AI best practices
- Ensure AI solutions comply with company security policies and industry regulations
- Implement access controls, data encryption, and secure APIs
Requirements:
- Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field; Master's or Ph.D. is a plus
- 3+ years of experience designing and implementing AI/ML solutions on Google Cloud Platform
- Google Professional Machine Learning Engineer certification is required
- Strong proficiency with GCP services such as Vertex AI, BigQuery, Cloud Dataflow, AI Platform, and AutoML
- Hands-on experience with machine learning frameworks like TensorFlow, Keras, and PyTorch
- Proficiency in programming languages such as Python, Java, or Go
- Experience with MLOps and CI/CD tools, including Cloud Build and Vertex AI Pipelines
- Strong understanding of AI/ML algorithms, data structures, and model optimization techniques
- Experience with containerization (Docker, Kubernetes) and orchestration using Google Kubernetes Engine (GKE)
- Strong analytical, problem-solving, and communication skills
- Experience with natural language processing (NLP) and computer vision solutions
- Experience with automated feature engineering and model interpretability
- Familiarity with data lake and data warehouse architectures on GCP
- Strong understanding of cloud security and access controls