Artificial Intelligence (AI) Engineer
Robert Half is hiring! We are looking for an experienced AI Engineer to join our team. In this role, you will play a pivotal part in developing cutting-edge machine learning solutions that enhance our SaaS platform and drive innovation. You will collaborate with cross-functional teams to create scalable AI systems that improve user experiences, automate operations, and expand product capabilities.
Responsibilities:
• Design and implement machine learning models, including predictive analytics and generative AI features, tailored for a modern SaaS platform.
• Build and optimize AI pipelines for data preparation, feature engineering, model training, evaluation, and deployment.
• Collaborate with product, data, and engineering teams to identify AI-driven opportunities that address business challenges.
• Develop cloud-based solutions using APIs, microservices, and containerized infrastructure to integrate machine learning models.
• Research and evaluate third-party AI tools and frameworks to enhance productivity and system functionality.
• Ensure AI systems adhere to privacy, security, and reliability standards while maintaining fairness and accuracy.
• Document workflows, maintain experiment logs, and establish reproducible processes for AI development.
• Stay informed about advancements in machine learning, generative AI, and SaaS architecture to apply best practices in projects.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
• Minimum of 3 years of experience deploying production-grade machine learning models.
• Proficiency in Python and familiarity with frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Hands-on experience with cloud platforms like AWS, Google Cloud, or Azure, and containerization tools such as Docker or Kubernetes.
• Knowledge of large language models (LLMs), vector databases, and modern AI/ML technologies.
• Understanding of microservice architectures and development processes.
• Strong foundation in data structures, algorithms, and software engineering principles.
• Experience with experimentation frameworks and tools for monitoring model performance.
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