Key Responsibilities

• Design, develop, and deploy machine learning and AI models at scale using GCP services
• Work with Databricks for data engineering and ML workflows
• Build and maintain containerized ML deployments using Kubernetes
• Develop and integrate Generative AI solutions using frameworks such as Hugging Face, LangChain, and OpenAI APIs
• Implement and monitor ML pipelines using Vertex AI, Cloud Monitoring, and Logging
• Design and maintain RESTful APIs and microservices architecture for ML model serving
• Apply distributed computing and big data processing techniques for large-scale data tasks
• Collaborate with cross-functional teams on end-to-end ML lifecycle management

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field
• 5+ years of experience in ML/AI development and deployment
• Strong programming skills in Python and ML libraries including scikit-learn, TensorFlow, and PyTorch
• Hands-on experience with GCP services and Databricks
• Proficiency in Kubernetes and containerized ML deployment
• Experience with Generative AI frameworks such as Hugging Face, LangChain, and OpenAI APIs
• Familiarity with GCP monitoring tools including Cloud Monitoring, Logging, and Vertex AI
• Strong understanding of distributed computing and big data processing
• Experience with RESTful APIs and microservices architecture

Skills Required