AI/ML Computational Scientist

Role Overview

We are seeking an AI/ML Computational Scientist who will be responsible for designing, building, and deploying AI and machine learning solutions tailored for enterprise-level clients. This role involves integrating bespoke models with cloud platforms and third-party AI services to produce solutions ready for production environments. The position covers the entire solution lifecycle from understanding client requirements and analyzing data to selecting and customizing models including Deep Learning, Generative AI, and Large Language Models (LLMs). Additionally, you will design scalable data and MLOps/LLMOps workflows to support training and production, ensuring high-quality, valuable, and reliable AI systems.

Key Responsibilities

• Translate real-world challenges into feasible, scalable AI and machine learning solutions.
• Develop machine learning algorithms, models, and computational frameworks while constructing scalable data pipelines enabling model training and operational deployment using DevOps and MLOps.
• Customize Deep Learning and Generative AI models according to specific business needs, available data, and system infrastructure requirements, including deployments on edge devices and high-performance computing platforms.
• Engage in research and development to advance AI algorithms, high-performance computing, and simulation models to tackle complex client problems.
• Handle extensive datasets and apply data preprocessing techniques to ensure the integrity and quality of input data for model training and deployment.
• Design and maintain efficient data storage and retrieval systems for models and knowledge bases using suitable technologies.
• Demonstrate and justify the business value and effectiveness of chosen model approaches.
• Collaborate closely with diverse teams, including business stakeholders, technical experts, engineers, architects, and UI/UX designers, to accomplish end-to-end project objectives and integrate AI solutions into production.

Education and Qualifications

• Bachelor's degree or equivalent qualification is mandatory.

Essential Skills and Experience

• Proven track record as a machine learning engineer or scientist with experience deploying scalable models in production environments, including aspects of monitoring, alerting, automatic bug reporting, and auditing.
• Strong knowledge of computer science fundamentals, including system architecture, system engineering, and programming.
• Experience working with distributed computing systems and architectures such as big data, high-performance compute, engineering simulations, scientific computing, grid and cloud computing, and distributed networks.
• Hands-on experience building and deploying AI/ML software solutions in cloud environments.

Preferred Skills and Qualifications

• Proficiency with Python and popular AI/ML frameworks and libraries like TensorFlow and PyTorch.
• Familiarity with language model APIs (e.g., large language models) and skills optimizing their performance for targeted applications.
• Experience with other programming languages such as C++, Java, R, and SQL.
• Excellent written and verbal communication skills with the ability to simplify complex technical concepts for non-technical audiences.
• Strong client-facing abilities, especially in consulting contexts.
• Demonstrated capability in cross-functional collaboration across internal and client teams.
• An entrepreneurial mindset fueled by curiosity and passion for emerging technologies and innovation.
• Advanced degrees (MS or PhD) in computer science, engineering, or related disciplines are advantageous.