Engineering AI Manager, Marigold

• You should have a firm grasp of modern software engineering, DevOps, and testing practices
• You should have a strong background in artificial intelligence and results driven leadership
• This role involves collaboration with product owners and stakeholders across time zones
• Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field, or equivalent combination of education and experience
• 7+ years of hands-on software development experience in Java or Python
• Experience with Large Language Models, Retrieval Augmented Generation, Embeddings, and Vector Databases in a production environment
• Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar
• Experience working with structured and unstructured data, and using advanced data preprocessing techniques
• Experience working in Agile or Lean teams, with a strong understanding of DevOps best practices (git, CI/CD, testing)
• Familiarity with containerization tools like Docker, Kubernetes, EKS/ECS
• Experience with data pipelines, ETL processes, and relational and NoSQL databases (e.g., MySQL, Clickhouse, MongoDB)
• Strong analytical, problem-solving, and communication skills, with the ability to explain complex technical concepts to non-technical stakeholders
• Experience working with AWS services like EC2, S3, Lambda, and Redshift
• Exposure to event streaming or pub/sub technologies like Kafka

Desirable

• We are seeking an AI/ML Manager to join our team to develop and implement AI-driven features and machine learning models that will drive the next generation of marketing automation combining generative AI, machine learning and engineering best practices
• Collaborate with product, engineering, and data science teams to design, develop, and deploy highly scalable solutions using generative AI and machine learning
• Build, manage and grow a mixed discipline team of data scientists, application developers, prompt engineers and quality engineers
• Develop and maintain software engineered in Python (and/or Java) integrating with large language models and data technologies such as Clickhouse, Apache Iceberg, and SageMaker Feature store
• Debugging flows across a complex environment; including troubleshooting eventing and ETL issues
• Write and maintain comprehensive unit and integration tests for the software you produce
• Optimize AI and machine learning models for accuracy, safety, performance and scalability