AI/ML Computational Science Engineer

What you'll do

• Formulate real-world business problems into practical, efficient, and scalable AI and machine learning solutions.
• Develop and implement machine learning algorithms, models, and computational systems for enterprise clients.
• Design and build scalable data pipelines to support model training and production using DevOps and MLOps.
• Customize and apply Deep Learning and Generative AI models based on specific business needs and infrastructure requirements.
• Conduct research and development on new AI algorithms, high-performance compute models, and simulations.
• Process large-scale datasets using preprocessing techniques to ensure high-quality input for training and production.
• Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge.
• Monitor and audit deployed models to ensure quality, reliability, and automated bug filing.

What we're looking for

• Bachelor's degree or equivalent (minimum 12 years work experience) or Associate's degree with 6 years experience.
• Minimum of 3 years of experience as a machine learning engineer or scientist deploying models in production at scale.
• Minimum of 3 years of experience applying theoretical foundations of computer science, system architecture, and system engineering.
• Minimum of 1 year of experience in distributed computing systems, big data, or high-performance compute.
• Minimum of 1 year of experience building and deploying AI/ML based software to a cloud environment.
• Proficiency in Python and python-based AI/ML frameworks like TensorFlow or PyTorch (preferred).
• Experience with LLM APIs and optimizing their usage for specific applications (preferred).
• MS or PhD in a related field such as computer science or engineering (preferred).